hematocrit – implications for bloodstain pattern analysis · hematocrit values, onto a ceramic...

HEMATOCRIT – IMPLICATIONS FOR BLOODSTAIN PATTERN ANALYSIS

Natasha ROGERS Bachelor of Science (Biology) Honours

Centre for Forensic Science University of Western Australia

This thesis is presented in partial fulfilment of the requirements for the Master of Forensic Science

September 2009

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DECLARATION

I declare that the research presented in this 36 point thesis, as part of the 96 point

Master degree in Forensic Science, at the University of Western Australia, is my own

work. The results of the work have not been submitted for assessment, in full or part,

within any other tertiary institute, except where due acknowledgement has been made in

the text.

…………………………………………………

Natasha Ellen Rogers

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ABSTRACT

Blood is one of the most common and important types of physical evidence present at a

crime scene. When liquid blood is acted upon by external physical forces, that blood is

often distributed through the air in the form of droplets, with bloodstains and bloodstain

patterns deposited on adjacent surfaces. Using the mathematical relationship that exists

between the blood droplet and resultant bloodstain’s length and width ratio, the angle at

which the blood droplet impacted the receiving surface can be determined. Using this

relationship, it becomes possible for Bloodstain Pattern Analysts to determine the three

dimensional Region of Origin for the blood source from which the bloodstains under

examination have originated. A Bloodstain Pattern Analyst performs angle of impact

calculations from bloodstains for the purpose of making a three dimensional

determination of blood source Region of Origin. The reliability of that determination is

based on an assumption that one of the most important biological properties of blood;

the amount of red blood cells or hematocrit value, has no influence over the length to

width ratio of a bloodstain. As a consequence the Impact angle = arcsine [width/length]

calculation has been assumed accurate regardless of the 'unknown' hematrocrit value.

This thesis investigated the effect of the hematocrit value on the angle of impact

calculation and thus the ability to determine the three dimensional blood source Region

of Origin.

Bloodstains were created by releasing a series of 18μL droplets, with ten different

hematocrit values, onto a ceramic tile at four different angles. The resultant bloodstain

length and width was measured and impact angle calculated. Evaluation of the research

data shows that the hematocrit value significantly affects the bloodstains length and

width. However, it is apparent that there is close agreement between the known and

calculated impact angles irrespective of the hematocrit value.

This thesis also examined bloodstain patterns with varying hematocrit values deposited

on adjacent vertical surfaces from impact spatter events. Five hematocrit values ranging

from 16.7 to 64.8% were used. The research showed that it is safe to conclude that a

Bloodstain Pattern Analyst is able to accurately determine the three dimensional Region

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of Origin for an impact spatter pattern regardless of the hematocrit value of the donor’s

blood.

This thesis compared the traditional manual measuring of bloodstains with a new

computer-based measurement technique that uses computer assisted ellipse fitting.

Bloodstains were measured manually and with the specifically designed Microsoft®

Office Excel 2003 Auto Shapes. The findings clearly demonstrate that the use of

Microsoft® Office Excel 2003 Auto Shapes to fit an ellipse and measure a bloodstain is

more accurate and reliable when compared to the current manual bloodstain

measurement technique.

The Tangent, String Line and BackTrack™ Images Methods are all current industry

accepted methods for determining the Region of Origin for impact spatter bloodstain

patterns. The impact angles of individual bloodstains are used to calculate the

horizontal and vertical location of the blood source [X, Y and Z coordinate values].

Results from this study suggest that all three reconstructive methods produce X, Y and

Z coordinate values [Region of Origin] within acceptable industry limits, thus allowing

for the positioning [laying, sitting or standing] of a victim during a bloodshed event.

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ACKNOWLEDGEMENTS

Dr Mark Reynolds: Firstly thanks Reno for having faith in me and allowing me to join

the secret world of BPA. You provided me with the technical guidance and support I

needed to complete this thesis. I was never scared of the red pen and have spent since

September 2006 “striving to comprehend”. They say that you are only ever as good as

your teacher, I was lucky, I got the best.

Professor Ian Dadour: Thanks Ian, it has been a long time coming but it is finally

finished. You have been nothing but supportive throughout this journey. I am truly in

your debt.

Senior Constable Brett McCance, WA Police Crime Scene Investigations: Thanks

Brett for all your support, advice and taking the time to help me reconstruct 15 impact

spatter patterns. If manual stringing ever becomes an Olympic sport I have no doubt

that we would get gold in the mixed doubles.

Hope Percy: Hope, thank you for taking the time to assist me with labelling 1200

bloodstains. Thanks for having the patience to support me for what has seemed like

eternity. Sunny days will no longer be spent studying but rather living.

Denise Galvin, PathWest: What can I say Denise, you are a truly inspiration woman

who originally gave up time in your busy schedule to help a stranger. You have

provided me with assistance every time I asked and if I have gained anything from this

experience it is a friend. I will always be there for you should you need it, my friend.

Kevin Davey, PathWest Laboratory Medicine WA Swan Districts: Thanks Kevin for

teaching me how to analyse my own blood and allowing your staff to take my blood for

experimental purposes.

All staff of PathWest Laboratory Medicine WA Swan Districts: Thanks for taking my

blood and showing general concern with the amount taken, especially when I said, “I

just need a little bit more.”

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Sasha Voss: Thanks Sasha for putting up with my moments of sheer panic after not

sleeping and trying to master stats.

Phil Freegard: Thanks for lending me the angle board to complete the passive drop

experiment.

Team Five, WA Police Crime Scene Investigations: Mick, Brett, Lamby and Wardy,

my boys, I spend more time with you guys than I do my family. Thanks for supporting

me throughout the last 18 months.

Fiona McQuisten: Fi, Sorry for making you revise Bloodstain Pattern Analysis but it is

truly appreciated.

My Family and Friends: All I can say is thanks and don’t worry I will be turning up to

the next do……….never shall you hear the words, “I can’t till I finish my masters”

again.

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TABLE OF CONTENTS

DECLARATION ............................................................................................................. ii

ABSTRACT .................................................................................................................... iii

ACKNOWLEDGEMENTS ............................................................................................ v

TABLE OF CONTENTS .............................................................................................. vii

LIST OF FIGURES ........................................................................................................ x

LIST OF TABLES ....................................................................................................... xiv

1. GENERAL INTRODUCTION TO BLOODSTAIN PATTERN ANALYSIS .. 1

1.1 Introduction ....................................................................................................... 1

1.2 Bloodstain Pattern Analysis .............................................................................. 1

1.3 History of Bloodstain Pattern Analysis ............................................................. 3

1.4 Aims and Objectives ......................................................................................... 5

2. LITERATURE REVIEW ....................................................................................... 7

2.1 Biological and Physical Properties of Human Blood ........................................ 7

2.1.1 Section Introduction ............................................................................... 7

2.1.2 Functions of Human Blood .................................................................... 7

2.1.3 Blood Composition ................................................................................. 8

2.1.4 Physical Properties of Blood ............................................................... 12

2.1.5 The Interaction between Biological and Physical

Properties of Blood ............................................................................. 18

2.1.6 The Use of Human Blood for Experimental Purposes ......................... 22

2.1.7 Section Conclusions ............................................................................. 23

2.2 Blood Dynamics .............................................................................................. 24

2.2.1 Section Introduction ............................................................................. 24

2.2.2 Blood Droplet Dynamics in Flight ....................................................... 24

2.2.3 Blood Droplet Impact Dynamics.......................................................... 28

2.2.4 Section Conclusions ............................................................................. 30

2.3 Reconstructive Techniques for Impact Spatter Patterns ................................. 31

2.3.1 Section Introduction ............................................................................. 31

2.3.2 Objectives of Bloodshed Reconstruction.............................................. 31

2.3.3 Terminology and Categories of Bloodstains ........................................ 32

2.3.4 Area of Convergence[AOC]................................................................. 34

2.3.5 Region of Origin [ROO] ...................................................................... 35

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2.3.6 Angle of Impact .................................................................................... 36

2.3.7 Measuring Bloodstains ........................................................................ 38

2.3.8 Stain Selection ...................................................................................... 41

2.3.9 The String Line Method........................................................................ 43

2.3.10 The Trigonometric [Tangent] Method ............................................... 43

2.3.11 The Computer Assisted [BackTrack™] Method ................................ 45

2.3.12 Section Conclusions ........................................................................... 45

3. THE EFFECT OF HEMATOCRIT VALUE ON RESULTANT STAIN

PARAMETERS .................................................................................................... 47

3.1 Experimental Methods .................................................................................... 47

3.1.1 Introduction .......................................................................................... 47

3.1.2 Collection and Handling of Blood ....................................................... 47

3.1.3 Adjusting Hematocrit Values ............................................................... 48

3.1.4 Angle Board ......................................................................................... 49

3.1.5 Experimental Setup .............................................................................. 50

3.1.6 Photographic Recording Technique .................................................... 50

3.1.7 Manual Measurements of Bloodstains ................................................. 51

3.1.8 Computer Assisted Bloodstain Measurement Using Microsoft® Office

Excel 2003 Auto Shapes ...................................................................... 51

3.1.9 Statistical Analysis ............................................................................... 52

3.2 Results ............................................................................................................. 53

3.2.1 Impact Angle ........................................................................................ 53

3.2.2 Stain Width ........................................................................................... 57

3.2.3 Stain Length ......................................................................................... 61

3.2.4 Manual versus Microsoft® Office Excel 2003 Auto Shapes

measurement techniques / hematocrit value comparison ................... 65

3.2.5 Manual versus Microsoft® Office Excel 2003 Auto Shapes

measurement techniques / impact angle comparison.......................... 65

3.2.6 Manual measurement technique – impact angle and hematocrit value

comparison .......................................................................................... 66

3.2.7 Microsoft® Office Excel 2003 Auto Shapes measurement technique –

impact angle and hematocrit value comparison ................................. 66

3.2.8 General observations ........................................................................... 67

3.3 Discussion ....................................................................................................... 69

3.4 Conclusions ..................................................................................................... 73

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4. THE EFFECT OF HEMATOCRIT VALUES ON IMPACT SPATTER

PATTERNS – IMPLICATIONS FOR RECONSTRUCTION ....................... 75

4.1 Experimental Methods .................................................................................... 75

4.1.1 Introduction .......................................................................................... 75

4.1.2 Collection and Handling of Blood ....................................................... 75

4.1.3 Adjusting Hematocrit Values ............................................................... 75

4.1.4 Experimental Setup .............................................................................. 76

4.1.5 Stain Measurement ............................................................................... 77

4.1.6 The Trigonometric [Tangent] Method ................................................. 78

4.1.7 The String Line Method........................................................................ 79

4.1.8 The BackTrack™ Method .................................................................... 80

4.1.9 Statistical Analysis ............................................................................... 81

4.2 Results ............................................................................................................. 82

4.2.1 Comparison of the X Coordinate ......................................................... 82

4.2.2 Comparison of the Y Coordinate ......................................................... 88

4.2.3 Comparison of the Z Coordinate ......................................................... 89

4.2.4 Comparison of the Stain Measurement Technique –

Tangent Method .................................................................................. 90

4.2.5 Comparison of Blood Hematocrit Value .............................................. 91

4.2.6 Comparison of the Coordinate Value .................................................. 91

4.2.7 Comparison of Reconstructive Technique ........................................... 91

4.3 Discussion ..................................................................................................... 102

4.4 Conclusions ................................................................................................... 105

4.5 Future Directions ........................................................................................... 105

6. BIBLIOGRAPHY ............................................................................................... 107

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LIST OF FIGURES

Chapter 2 Page

Figure 2.1 Components of whole human blood ........................................................ 9

Figure 2.2 Formation of a blood clot showing the red blood cells (red),

activated platelets (blue) and fibrin strands (yellow). .............................. 9

Figure 2.3 Representation of surface tension on the surface and cohesion

throughout a spherical droplet. ............................................................... 14

Figure 2.4 Influence of temperature on the surface tension of whole blood ........... 16

Figure 2.5 Effect of hematocrit on blood viscosity flowing through small

and large tubes........................................................................................ 18

Figure 2.6 Influence of hematocrit value on the relative viscosity of whole

human blood compared with that of plasma. ......................................... 19

Figure 2.7 Parabolic flight path position instants for a droplet with

gravitational force indicators (blue arrows) and air resistance

(pink arrows). ......................................................................................... 26

Figure 2.8 Prolate, spherical and oblate forms of an oscillating blood droplet

during flight ............................................................................................ 27

Figure 2.9 Major Bloodstain Pattern Categories. .................................................... 33

Figure 2.10 Bloodstain pattern analysis “Spatter” sub categories ............................. 34

Figure 2.11 Two dimensional Area of Convergence determination from

multiple bloodstains originating from a single impact ........................... 35

Figure 2.12 The X, Y and Z coordinate values. ........................................................ 36

Figure 2.13 Width to length ratio of a bloodstain equated to a right angle

triangle.................................................................................................... 37

Figure 2.14 Directionality of bloodstain established with location of the

leading and terminal edges ..................................................................... 39

Figure 2.15 Measurement of the width and length of an elongated bloodstain

by fitting a theoretical ellipse ................................................................. 40

Figure 2.16 Measurement of the width and length of a bloodstain using

Microsoft® Office Excel 2003 Auto Shapes ........................................... 41

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Chapter 2 (cont) Page

Figure 2.17 Basic right angled triangle and how this can be used by a

Bloodstain Pattern Analyst to determine the area of origin for a

impact pattern on a wall ......................................................................... 44

Chapter 3

Figure 3.1 Comparative impact angle for bloodstains created at known

impact angles with different hematocrit values, manually

measured and measured using Microsoft® Office Excel Auto

Shapes [Error bars represent ±1 Std Dev]. ............................................. 56

Figure 3.2 Comparative width analysis for bloodstains created at known




Figure 3.3 Comparative length analysis for bloodstains created at known




Figure 3.4 Impact angle, hematocrit value and stain shape. .................................... 68

Chapter 4

Figure 4.1 Author manually measuring the width and length of a bloodstain

using electronic calipers and OptiVisor headset .................................... 78

Figure 4.2 Stringing of a impact spatter pattern showing the estimated

Region of Origin in yellow .................................................................... 79

Figure 4.3 An example of a individual stain, with scale, plumb line and

major axis line photographed for use in both BackTrack™

Images and Microsoft® Office Excel 2003 Auto Shapes. ...................... 80

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Figure 4.4 Difference between the known and calculated X coordinate value

using the Tangent, String Line and BackTrack™ Methods to

determine the Region of Origin for 15 impact spatter patterns

with differing hematocrit values. ........................................................... 84

Figure 4.5 Difference between the known and calculated Y coordinate value




Figure 4.6 Difference between the known and calculated Z coordinate value




Figure 4.7 Difference between the known and calculated X coordinate value

using the Tangent Method for bloodstains measured using

Microsoft® Office Excel AutoShapes, Manual and BackTrack™

for 15 impact spatter patterns with differing hematocrit values. ........... 87

Figure 4.8 Impact Spatter Pattern 2 (16.7 Hematocrit) – actual blood source

Z value indicated. ................................................................................... 95

Figure 4.9 Impact Spatter Pattern 2 (16.7 Hematocrit) – Comparison of

experimentally derived Z coordinate values with actual blood

source Z coordinate value. ..................................................................... 95


experimentally derived X coordinate values with actual blood

source X coordinate value. ..................................................................... 96


experimentally derived Y coordinate values with actual blood

source Y coordinate value. ..................................................................... 96

Figure 4.12 Impact Spatter Pattern 2 (16.7 Hematocrit) – wooden blood

source support positioned as to indicate the actual blood source

location top of blood. ............................................................................. 97

Figure 4.13 Impact Spatter Pattern 15 (64.8 Hematocrit) – actual blood

source Z coordinate value indicated. ...................................................... 98

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experimentally derived Z coordinate values with actual blood

source Z coordinate value. ..................................................................... 98


experimentally derived X coordinate values with actual blood

source X coordinate value. ..................................................................... 99

Figure 4.16 Impact Spatter Pattern 15 (64.8 Hematocrit) – wooden blood

source support positioned as to indicate the actual blood source

location top of block............................................................................... 99


experimentally derived Y coordinate values with actual blood

source Y coordinate value. ................................................................... 100

Figure 4.18 Top view 2D representation of Impact Spatter Pattern 15 (64.8

Hematocrit) using BackTrack™. The red cross indicates the X

and Y coordinates. ................................................................................ 100

Figure 4.19 Side view 2D representation of Impact Spatter Pattern 15 (64.8

Hematocrit) using BackTrack™. The red cross indicates the X

and Z coordinates. ................................................................................ 101

Figure 4.20 End view 2D representation of Impact Spatter Pattern 15 (64.8

Hematocrit) using BackTrack™. The red cross indicates the Y

and Z coordinates. ................................................................................ 101

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LIST OF TABLES

Chapter 2 Page

Table 2.1 Surface tension of some common fluids. ............................................... 15

Table 2.2 Hematocrit values (percent) for males and females throughout

childhood ................................................................................................ 22

Table 2.3 Normal hematocrit values for a variety of mammalian species ............. 22

Chapter 3 Table 3.1 Volumes of plasma and red blood cells pipette into labeled vials

with the corresponding predicted hematocrit value versus the

actual hematocrit value used for experimental purposes. ...................... 49

Table 3.2 Shows Manual and Microsoft® Office Excel Auto Shapes

(BOLDED) mean calculated impact angle, standard deviation

and minimum-maximum range for bloodstains with different

hematocrit values that have fallen on ceramic tiles offset from a

vertical at known angle values (n = 30 stains). ...................................... 55


(BOLDED) mean width (mm), standard deviation and minimum-

maximum range for bloodstains with different hematocrit values

that have fallen on ceramic tiles offset from a vertical at known

angle values (n = 30 stains). ................................................................... 59


(BOLDED) mean length (mm), standard deviation and

minimum-maximum range for bloodstains with different

hematocrit values that have fallen on ceramic tiles offset from a

vertical at known angle values (n = 30 stains). ...................................... 63

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Chapter 4 Page Table 4.1 Predicted hematocrit value versus the actual hematocrit value

used for experimental purposes for plasma and red blood cells. ........... 76

Table 4.2 Shows Microsoft® Office Excel Auto Shapes, Manual

(BRACKETS) and BackTrack™ (BOLDED) measurement data

for bloodstains to determine Region of Origin using Tangent,

String Line and BackTrack™ Methods for Impact Spatter Pattern

1 to 15. .................................................................................................... 83

Table 4.3 Shows Manual, Microsoft® Office Excel Auto Shapes (ITALICS),

BackTrack™ (BOLDED) measurement data for bloodstains for

Impact Spatter Patterns 1 to 15. ............................................................. 93

1

1. GENERAL INTRODUCTION TO BLOODSTAIN PATTERN ANALYSIS

1.1 Introduction This chapter introduces the topic of Bloodstain Pattern Analysis (BPA). Using the

available information in published literature, a brief history of BPA along with its

development of BPA as a forensic discipline will be discussed, including how such

scientific evidence has been evaluated by judicial proceedings. The last section details

the purpose and aims of this research thesis.

The reconstruction of a bloodshed event has become synonymous with experimentation

in an effort to understand general blood dynamics and recreate bloodstain patterns

which are substantially similar to those found at a crime scene (Wonder 2001).

Currently, no blood source Region of Origin reconstructive methods take into account

the unknown hematocrit value of bloodstains and the possible effect of hematocrit

values on the reliable determination of that Region of Origin. The purpose of this study

is to identify the effect of hematocrit values on resultant stain parameters and assess the

level of uncertainty with regards to reconstruction of a bloodshed event at crime scenes.

The quantification of this uncertainity will give scene and experimental results

increased reliabilty, traceability and scientifc robustness as required by the courts

(Daubert 1993).

1.2 Bloodstain Pattern Analysis

Blood is one of the most common and important types of physical evidence present at a

crime scene (Raymond et al. 2001). When blood is acted upon by external physical

forces, the blood is often distributed through the air in the form of droplets. This results

in bloodstains and bloodstain patterns deposited on adjacent surfaces. A crime scene

investigator can gain valuable information from serology, immunology and

interpretation of bloodstains and bloodstain patterns (Pizzola et al. 1986a).

2

BPA involves the analysis of the size, shape and distribution of the bloodstains and

bloodstain patterns. This combined with knowledge of the underpinning sciences

(mathematics, biology and physics) provides information on the event or sequence of

events that resulted in the deposition of these bloodstains and patterns (Bevel and

Gardner 2002; MacDonell 2005; James et al. 2005). A bloodstain analyst is required to

examine the incident scene, take photographs, make sketches, examine clothing,

objects, weapons, and deceased individuals and read forensic pathology and biology

reports in significant detail (James et al. 2005). Bloodstains provide analysts with a

“window to the past” (Bevel and Gardner 2002), defining actions that have occurred

during the bloodshed event. After viewing all the evidence available the bloodstain

analyst will draw conclusions and produce a bloodstain pattern report that may be

presented for judicial proceedings as expert testimony.

Raymond et al. 2001; Bevel and Gardner 2002; James et al. 2005 state that the crime

scene reconstruction of a bloodshed event can provide information to determine:

• Areas of convergence and origin of bloodstains

• Type and direction of impact

• Mechanisms by which bloodstains and bloodstain patterns were produced

• Provide an understanding as to how blood was deposited onto particular items of

evidence

• The position of the victim, assailant, or items located within the scene during the

bloodshed event

• Possible movement of the victim, assailant, or items post bloodshed event

• Support or contradict statements given by the victim, assailant or witnesses

about the event

• Support, contradict or provide additional information for post mortem findings

• Correlation with other laboratory findings relevant to the investigation

The Federal Bureau of Investigation examiner training program (2004) states that the

basic purpose of bloodstain analysis is to identify the sequence in which the bloodstains

and bloodstain patterns are produced. These bloodstain patterns can yield valuable

information concerning the events which led to their creation. The information gained

can then be used for the reconstruction of the incident.

3

Reconstruction and experimentation of a bloodshed event can range from simplified

exercises such as walking in blood, dropping blood from a pipette onto various types of

fabrics or to the design of elaborate computer systems to assist the bloodstain analyst

with stain measurements and virtual stringing. This experimentation and subsequent

reporting to the bloodstain community allows the behaviour of blood and its associated

limitations to be understood. Experiments must be designed with consideration given to

materials, methods and replication. This limits areas of uncertainty and error giving the

results the traceability, and if found to be reliable, acceptance by the courts (Makita

2001). Furthermore, the reconstruction must be used in conjunction with an

understanding of the science [mathematics, biology, physics and chemistry] (Eckert and

James 1998).

1.3 History of Bloodstain Pattern Analysis

As to the issue of being a “new” discipline, the examination and consideration of

bloodstain patterns and their historical acceptance in forensic science is well

documented (Bevel and Gardner 2002).

One of the first studies of Bloodstain Pattern Analysis is credited to a Polish scientist

Dr. Eduard Piotrowski in 1895. Dr Piotrowski’s work ‘Uber Entstehung, Form,

Richtung und Ausbreitung der Blutspuren nach Hiebwunden des Kopfes’ translates to

‘Concerning the Origin, Shape, Direction and Distribution of the Bloodstains Following

Head Wounds Caused by Blows’ (James et al. 2005). Piotrowski’s experiments utilised

live rabbits as a blood source and applied a variety of impact methods including a

hammer, stone and hatchet to provide key elements of BPA including the shape, size

and distribution of bloodstains in cast off and spatter patterns (MacDonell 1993).

In 1939 Balthazard et al. delivered a paper at the XXII Congress of Forensic Medicine

titled ‘Etude des Gouttes de Sang Projecte’ or ‘Research of Blood Spatter’. Balthazard

et al. (1939) has been attributed as the first to recognise the length to width ratio of a

bloodstain as being a function of the angle at which a blood droplet impacts a receiving

surface. This research established the basis for current stringing techniques and first

identified the effect of surface texture on the formation of bloodstains (Eckert and

James 1998; Bevel and Gardner 2002; James et al. 2005).

4

In 1953 Dr Paul Kirk published the book ‘Crime Investigation’ in which was the

chapter ‘Blood Physical Investigation’, which discussed the application of BPA with

respect to crime scenes. In 1955 Kirk prepared an affidavit for the case State of Ohio

vs. Samuel Sheppard. Prepared for the Court of Common Pleas, this expert evidence

was considered a significant milestone, paving the way for the application of BPA in

courts of law. In this affidavit Kirk describes the position of the accused, the victim at

the time of the bloodshed event, and the hand which had administered the blows (Bevel

and Gardner 2002; James et al. 2005).

In 1960 three basic categories of bloodstains and bloodstain patterns emerged in a

publication by Dr Jozef Radziki; ‘Saldy Krwi w Praktyce Sledczej’ which translates as

‘Bloodstain Prints in the Practice of Technology’. These categories were based on their

mechanism of construction and recorded by Bevel and Gardner (2002) as:

• Bloodstains resulting directly from extravasation – Drops, gushes, and pools of

blood

• Bloodstains resulting from the application of various instruments – spatter, cast-

offs, and pattern resulting from direct contact

• Bloodstains resulting from wiping or removal of blood

In the 1960’s BPA started to become recognised as a forensic discipline, with Professor

Herbert Leon MacDonell completing extensive worldwide research, resulting in the

documentation of over five hundred science based references relating to bloodstain

patterns and their analysis. These references were written in a variety of languages

including English, German, French, Spanish, Italian, Japanese, Russian, Hungarian and

Polish, with the earliest reference dating back to 1514.

In 1971 MacDonell conducted extensive research using a Law Enforcement Assistance

Administration (LEAA) grant and co-authored ‘Flight Characteristics and Stain

Parameters of Human Blood’ (MacDonell and Bialousz 1971). This was closely

followed, in 1973, by MacDonell’s first formal bloodstain training course and

associated laboratory manual. Since then hundreds of people have been trained in both

basic and advanced BPA courses (Eckert and James 1998; Bevel and Gardner 2002;

James et al. 2005).

5

In 1983 the International Association of Bloodstain Pattern Analysis [IABPA] was

founded by MacDonell and other Bloodstain Pattern Analysts. The IABPA promotes

the knowledge, training, education, techniques and general understanding of BPA. The

IABPA has more than 800 members worldwide and publishes quarterly newsletters to

allow members to keep up to date with contemporary BPA issues. In 2002 the Federal

Bureau of Investigation funded the formation of a scientific working group on BPA

called the Scientific Working Group on BPA [SWGSTAIN]. SWGSTAIN addresses

issues within the BPA discipline including education, training, legal, quality assurance,

research, taxonomy and terminology. Since the inception of IABPA in 1983, and the

development of SWGSTAIN in 2002, significant advancements in BPA have been

achieved, with numerous publications written to assist and guide the bloodstain analyst

(James et al. 2005).

1.4 Aims and Objectives

At present no research has been undertaken to determine the effect of the biological

properties of blood on the reconstruction of impact bloodshed events. This thesis aims

to examine the effect of one biological property of blood. The main objectives of this

study are:

(i) To determine the effect of hematocrit value on the angle of impact

calculation theory using single drop experimentation (Chapter 3).

(ii) To examine any error associated with the calculation of angle of impact for

bloodstains generated with different blood hematocrit values using both

manual and computer assisted measurement techniques (Chapter3).

(iii) To determine if the ability to predict the ‘Region of Origin’ of the blood

source is influenced by hematocrit value. This will be conducted using

three different industry accepted reconstruction methods: the String Line

Method [combined with Microsoft® Office Excel 2003 Auto Shapes], the

Tangent Method [combined with Microsoft® Office Excel 2003 Auto

Shapes] and computer assisted Directional Analysis Method [BackTrackTM

Images] (Chapter 4).

6

There are two hypotheses that this thesis will test:

1. If the impact angle calculation is related to the hematocrit value [amount of red

blood cells] then varying the hematocrit value should result in a deviation of

the experimental impact angle from the expected impact angle.

2. If the impact angle calculation is affected by the hematocrit value then the

ability of the analysts to reliably determine the three dimensional Region of

Origin for a blood source will also be affected.

7

2. LITERATURE REVIEW

2.1 Biological and Physical Properties of Human Blood 2.1.1 Section Introduction

This section will describe the biological and physical properties of blood. The

functions, composition, use of blood for experimental purposes, physical properties and

their interaction will be discussed in detail. For BPA a fundamental understanding of

the physical and biological properties of blood is necessary for the correct interpretation

of bloodshed events (Bevel and Gardner 2002).

2.1.2 Functions of Human Blood

It has long been recognised that blood is a truly unique substance that is the essence of,

and essential in, maintaining life (Marieb 2003). To date nothing artificially

manufactured has been able to replace blood and maintain life. One of the first written

accounts about blood can be attributed to Hippocratic writings from about 400 B.C.

which describe the body as a composite of four humors; black bile, blood, phlegm and

yellow bile. Ill health and disease were thought to be caused by upset in the balance of

these humors (McKenzie 1988). Modern medicine now recognises that a difference in

blood composition is a valid indicator of disease rather than the cause (McKenzie

1988).

Blood is a complex biological fluid that has the primary role of oxygen transportation

about the body. In addition, it performs the vital function of waste removal. Blood also

plays a significant role in wound healing as it is the primary carrier of immunity

responders and mediators of inflammation. Blood loss is prevented by a process known

as hemostasis (Dailey 2001). Hemostasis occurs via Vascular Spasm

[vasoconstriction], Platelet Plug Formation, Coagulation Protein Activation and Clot

Lysis [slow dissolution] (James et al. 2005). When these functions are not effective,

blood is lost from the closed vascular system to its external environment and can be

determined to be a blood shedding event.

8

2.1.3 Blood Composition

2.1.3.1 Introduction

Blood makes up an average of 7% to 8% of the human body weight [70ml ± 10ml per

kg of body weight] with average blood volumes ranging between four to five litres in

females and five to six litres in males (Eckert and James 1998). Blood is basically a

fluid with a suspension of solid particles [formed elements] in a liquid component

[plasma] (Ciofalo et al. 2002). With the invention of the microscope the varying

cellular components of blood were recognized and in 1852 Karl Vierordt published the

first quantitative blood cell analysis results (McKenzie 1988). There are three types of

formed cellular elements in blood [red blood cells, white blood cells and platelets],

which account for approximately 45% of total blood volume; the plasma component

contributes the remaining 55% (Rodak 2002). For every 500 red blood cells there are

about 30 platelets and 1 white blood cell (Passmore and Robson 1968). Erythrocytes

[red blood cells], leukocytes [white blood cells] and thrombocytes [platelets] are

morphologically different with each type of cell performing a set of specialized

functions within the body (Dailey 2001). The various components of whole blood can

be seen in Figure 2.1 and formation of a blood clot in Figure 2.2. After birth and

throughout life, mature blood cells are ‘made’ by the process of hematopoisis in the

bone marrow stem cells (Rodak 2002).

2.1.3.2 Red Blood Cells

Red blood cells [erythrocytes or red corpuscles] contain hemoglobin and transport

oxygen from the lungs throughout the body via the closed circulatory system. There are

approximately 4.2 x 106 – 6.2 x 106 red blood cells per mm3 of blood. This accounts for

99% of the formed element component. Woodcock (1976) estimates that 70% of a red

blood cell is water and 30% is hemoglobin. Red blood cells are non-nucleated, flexible,

bi-concave disks with a diameter of 7μm and a thickness of 2μm (Dailey 2001). The

volume of red blood cells varies between 80 x 10-15 to 100 x 10-15 L (McKenzie 1988).

Oxygenated blood travels via the arterial system, and is bright red in colour due to its

richness in hemoglobin. Blood containing carbon dioxide is returned to the lungs for re-

oxygenating via the venous system. The blood returning to the lungs is recognised by

being darker blue in colour due to the hemoglobin / carbon dioxide combination (James

et al. 2005).

9

Figure 2.1 Components of whole human blood (James et al. 2005:43).

Figure 2.2 Formation of a blood clot showing the red blood cells (red), activated platelets

(blue) and fibrin strands (yellow) (James et al. 2005:48).

10

The flexibility of a red blood cell is attributed to the complex chemical structure and

composition of its cellular membrane. The area of the flexible membrane is larger than

the minimum required to hold the cellular contents (Jay 1973), thus the membrane has

the ability to deform and change shape from 7μm to 3μm to assist flow in the small

capillaries such as those that exist within the spleen (McKenzie 1988). Damage or

alteration to the cellular membrane will cause premature death of the cell as red blood

cells lack the enzymes and cellular organelles required for cellular repair (McKenzie

1988).

Because red blood cells are non-nucleated they cannot be used for Deoxyribonucleic

Acid [DNA] analysis and do not undergo cellular division (Gardner 2005). The lifespan

of a red blood cell is 100 to 120 days. Red blood cells are heavier than plasma and this

can be seen when blood is left standing or has undergone centrifuging. This increased

weight can also be observed after death with the settling of the red blood cells, under

gravity, to the lowest region in the body. This settling is known as post mortem lividity

(Chmiel and Walitza 1980).

2.1.3.3 White Blood Cells

White blood cells [leukocytes or white corpuscles] fight infection and destroy old

cellular material. They can be divided into two sub-categories granulocytes and

nongranulocytes. Granulocytes are produced in the primitive stem cells in the bone

marrow and include neutrophils, eosinophils, and basophils, whereas nongranulocytes

are produced in the lymph nodes and include lymphocytes and monocytes. Each type of

white blood cell has a specific role to locate and destroy antigens [i.e. bacteria, viruses,

parasites] (Dailey 2001).

There are 4.5 x 103 – 11 x 103 white blood cells per mm3 of blood. Lower levels are

often observed in elderly individuals (Dailey 2001). Due to the relatively low number

of white blood cells, they have little effect on the physiological flow properties of

blood. They are the only nucleated cells within the cellular components of blood, thus

providing usefulness in both nucleic and mitochondrial DNA analysis for forensic

purposes (Gardner 2005).

11

2.1.3.4 Platelets

Platelets [thrombocytes] are the final cellular component of blood. The role of platelets

in blood coagulation was first established by Bizozero in 1882 (McKenzie 1998).

When platelets detect a damaged vessel they undergo a morphological response by

increasing in size and becoming adhesive to form a platelet plug (Dailey 2001).

Platelets amass at the damaged vessel wall creating a platelet plug that attempts to

restrict or stop blood flow from the circulatory system. Platelets develop in bone

marrow, are discoid in shape and range in size from 2μm to 4μm. Like red blood cells

platelets are non-nucleated cells and are unsuitable for DNA analysis. There are

approximately 150 x 103 – 450 x 103 platelets per mm3 of blood. The low percentage of

platelets in whole blood means they have little effect on the physical properties of blood

flow other than during a hemostatic event (Ganong 1991).

2.1.3.5 Plasma

Blood plasma is extra-cellular material that is the non-living liquid component of blood.

Plasma provides the medium for circulation allowing the transportation of blood cells

and solutes to the required tissue. Plasma accounts for approximately 4% of an

individual’s body weight or about 3.2 litres for an 80 kg adult. Plasma is comprised of

approximately 91% water, 8% soluble protein, 1% organic acids and salts (Bevel and

Gardner 2002). Albumin accounts for 60% of the plasma protein and contributes to

osmotic pressure (Marieb 2003). One type of protein is fibrinogen, which after physical

disruption of the blood vessel, is converted to fibrin and forms a gelatinous mass [clot]

(James et al. 2005). To provide stability, the formed clot undergoes constriction to

squeeze out the liquid plasma. Once the clotting factors are removed from plasma by

constriction, the liquid is then called serum and can be seen as a pale yellow liquid

around a retracted blood clot (Eckert and James 1998; James et al. 2005). From a

rheological perspective if the cellular component of blood is removed, the non living

plasma can be regarded as a Newtonian fluid and has a viscosity about 1.6 times that of

water (Ciofalo et al. 2002).

12

2.1.4 Physical Properties of Blood

2.1.4.1 Introduction

Students undertaking high school chemistry are taught that a liquid has a definite

volume but no shape, with liquids having the ability to flow and assume the shape of

their holding vessel (Zumdahl 1989). Vogel (1996) suggests ‘a fluid is just a synonym

for a liquid’ whilst Walker (2000) defines a fluid as: ‘any gas, liquid or particulate

solid that flows and can offer no permanent resistance to change of shape’.

The study of fluid deformation and flow is called Rheology and is inclusive of fluid

properties such as elasticity, plasticity, viscosity and Newtonian / Non-Newtonian

behaviour. BioRheology is the specialised study of the fluid dynamics of biological

fluid, including blood (Vogel 1996). Blood and other biological fluids are defined by

Vogel (1996) as complex, multidimensional continuum of Non-Newtonian fluids and

viscoelastic solids. To provide a basic understanding of blood dynamics with respect to

blood droplets during flight and the subsequent impact by a blood droplet with a

receiving surface the following physical properties will be discussed:

• Newtonian and Non-Newtonian Fluid Behaviour

• Surface Tension

• Relative Density

• Viscosity

2.1.4.2 Blood - A Non-Newtonian Fluid

A Newtonian fluid shows a linear relationship between applied shear stress and strain

rate [resultant deformation] (Vogel 1996). Water, petrol and ink are common examples

of Newtonian fluids and when the cellular components of blood are removed, the

remaining plasma can be regarded as a Newtonian fluid. In Non-Newtonian fluids such

as oil and paint the shear stress and strain rate are non linear, thus there is no constant

coefficient for viscosity (Vogel 1996).

13

Blood is also a Non-Newtonian fluid with its suspension of elastics cells [red blood

cells] in fluid [plasma] and a dynamic viscosity that is not dependent on shear strain

rate. Blood does not obey Newton’s Law, meaning that shear stress is not proportional

to the shear rate (Eckmann et al. 2000). Shear is a type of deformation in which parallel

planes in a volume of material remain parallel but are only displaced with respect to

each other. Measurement of viscosity of Non-Newtonian fluids is considered

meaningless unless it is related to the rate of shear under which the viscosity

measurement was taken (Ford and Furmidge 1963).

Blood exhibits complex rheological properties, such as viscoelasticity [because of its

viscous behaviour], elasticity [due to the deformation of red blood cells], thixotropic

response [the longer the fluid undergoes shear stress the lower the viscosity] and shear

thinning [decreasing viscosity with increased shear rate]. The viscoelasticity,

thixotropic and shear thinning behaviour of blood are all derived from the

microdynamics of the red blood cells (Ciofalo et al. 1999).

2.1.4.3 Surface Tension

Drop formation of a Non-Newtonian fluid such as blood can be attributed to the

following:

• surface tension [forces acting on the surface]

• cohesion [attractive forces between like molecules acting within the blood]

• viscosity (Wonder 2001)

This is shown in Figure 2.3.

14

Figure 2.3 Representation of surface tension on the surface and cohesion throughout a

spherical droplet (Wonder 2001:27).

Surface tension results from the molecules at the surface of the liquid experiencing a net

force directionally into the liquid, thus the unbalanced molecular cohesive forces near

the surface of the liquid give the appearance that the liquid surface is covered by an

elastic membrane (James et al. 2005).

Within the body, blood surface tension is considered a crucial part of many vital

functions, but few publications exist examining blood surface tension in any detail

(Rosina et al. 2007). This may be due to the fact that most studies investigate factors

effecting blood flow in a closed vessel of fixed diameter and its impact for

cardiopulmonary anaesthesia (Guber et al. 1999; Paut and Bissonnette 2001). In a

forensic context, Raymond (1997) suggests that the physical effect of surface tension in

a blood droplet upon leaving the body is also crucial. Surface tension is measured in

newtons per meter [N/m] and is the energy required to stretch a unit of change of a

surface area at the blood droplet’s surface and air interface (Raymond et al. 1996). In

the absence of any opposing forces, surface tension will form a drop of liquid into a

sphere, as a sphere offers the smallest surface area for a definite volume and prevents

the droplet from separating (Dillard and Goldberg 1978). Surface tension is expressed

as a force per unit length. Blood has a surface tension of 50dyn/cm whilst water is

72.5dyn/cm at 20°C (James et al. 2005). Raymond (1997) states that both the flight of

15

the blood droplet through air and the shape of the stain on the receiving surface are

directly influenced by surface tension.

Table 2.1 Surface tension of some common fluids (James et al. 2005:52).

Common Fluids Typical Surface Tension @ 20°C

(dynes/cm)

Ethanol 22.3

Soap 25

Olive Oil 32

Blood 50

Glycerine 63.1

Water 72.5

Mercury 465.0

The average blood temperature for a healthy adult is 37°C (Marieb 2003). Rosina et al.

(2007) investigated the effect of temperature on surface tension of blood for fifteen

human subjects. The influence of an increase in temperature of the blood resulting in a

decrease in the surface tension is shown in Figure 2.4. The results published by Rosina

et al. (2007) were further supported by Hrncir and Rosina (1997), who found a

significant, inverse linear relationship between surface tension and temperature which

could not be correlated to age, sex, red cell sedimentation rate, blood hemoglobin levels,

cholesterol or the number of red blood cells. Rosina et al. (2007) concluded that surface

tension monitoring in patients could assist in the appropriate adjustment of rheological

pharmaceuticals for different areas of biomedical investigations.

16

Figure 2.4 Influence of temperature on the surface tension of whole blood (Rosina et al. 2007).

2.1.4.4 Relative Density

With respect to a fluid, the term relative density [which has replaced the term specific

gravity (James et al. 2005)] is the measure of its weight per unit of volume (d = m/v).

Whole human blood has a density of 1.060g/cm3, which is higher than that of water

which has a relative density of 1.0g/cm3 (James et al. 2005).

2.1.4.5 Viscosity

Kalbunde (2005) states that the internal friction of adjacent layers sliding past one

another in a liquid, as well as the friction generated between the fluid and the wall of the

vessel, is called viscosity. The frictional force that exists between adjacent layers of

fluid as they move past one another creates the resistance to flow (Chaplin 2007). A

deformation [shear strain] occurs when force [shear stress] is applied to a volume of

material (Chaplin 2007). Increasing the concentration of a dissolved substance in a

fluid generally increases the viscosity (Chaplin 2007). For example increasing the

number of red blood cells suspended in a constant volume of plasma medium makes the

blood thicker thus increasing its viscosity.

17

There are several different coefficients of viscosity within a fluid. Vogel (1996)

describes dynamic viscosity with respect to a stack of individual sheets of paper.

Dynamic viscosity is the friction encountered between the sheets and can be referred to

as the interlamellar stickiness of the fluid. Dynamic viscosity is shortened to viscosity,

but is sometimes referred to as absolute viscosity. If the dynamic viscosity of a fluid is

independent of shear strain rate the fluid is defined as Newtonian and if the shear strain

rate was plotted against shear stress the resultant graph would be linear passing through

the origin (Kim 2002; Chaplin 2007). Blood is a Non-Newtonian fluid with viscosity

depending on shear rate, with viscosity decreasing as the shear rate increases (Wonder

2001; Eckmann et al. 2000). The ratio of dynamic viscosity to density is called

Kinematic Viscosity (Vogel 1996).

Viscosity [η] can be defined as Equation 2.1

η = shear stress [Pa s] shear rate The units are either pascal seconds [Pa s] or the poise [P]

The viscosity of blood undergoing circulation is dependenton the shear rate within the

vessel it is travelling, that is the size of the vessel through which it flows. This is

known as the Fahraeus-Lindquist effect (Eckmann et al. 2000; Paut and Bissonnette

2002). For example, in large arteries with large blood flows the shear rates are high

compared to shear rates in microcirculation (Eckmann et al. 2000). Blood flowing

through a vessel of 2mm in internal diameter has a viscosity that is close to plasma

(Paut and Bissonnette 2002). The ability of blood to change viscosity according to the

vessel through which it is flowing has been attributed to the colloidal properties [the

suspension of cells within plasma] of blood which prevent clumping or coagulation.

Figure 2.5 shows the effect of hematocrit percent on blood viscosity through two

different size vessels.

18

Blood traveling within blood vessels undergoes a process known as stratified axial

streaming (Wonder 2001). The red blood cells cluster along the blood vessel core,

whilst the plasma and platelets circulate around the circumference closer to the

endothelium. Most of the friction in a flowing fluid occurs near the endothelium where

the rate of shear is higher. The different layers travel through a vessel at different

velocities thus experiencing different viscosities. The axial streaming reduces the

power required for blood to travel around the circulatory system (Johnson 1999), and

provides stability reducing turbulence and preventing droplet instability (Wonder 2001).

Figure 2.5 Effect of hematocrit on blood viscosity flowing through small and large tubes

(Johnson 1999:135).

2.1.5 The Interaction between Biological and Physical Properties of Blood

2.1.5.1 Hematocrit Value and Viscosity

Different fluids have different viscosity. Blood is 5 times more viscous than water

(Marieb 2003) and plasma is about 1.6 times the viscosity of water at 37°C (Kalbunde

2005). However, blood viscosity is not constant (Lowe 1988) and is dependenton

hematocrit percent, plasma, time, temperature and shear rate (Johnson 1999; Wonder

19

2001; Eckmann et al. 2000; Paut and Bissonnette 2002). Therefore, viscosity is

considered a function of hematocrit value (Raymond 1997; Bevel and Gardner 2002).

Wonder (2001) stated that two components, the plasma and the red blood cells, are

important for BPA. The volume of red blood cells in relation to the volume of plasma

is commonly expressed as a percentage called Hematocrit [Hct] or Packed Cell Volume

[PCV] (Rodak 2002). In adults, hematocrit values can range from 35% to 54%. The

hematocrit value can be used as a rough indictor for the oxygen carrying capacity of

blood (Dailey 2001).

The Fahraeus-Lindquist effect confirms that the viscosity of whole blood varies with the

hematocrit value (Johnson 1999; Paut and Bissonnette 2002). As the hematocrit value

increases there is a disproportional increase in viscosity; for example a 50% increase in

the hematocrit value can result in a 100% increase in blood viscosity. At a hematocrit

value of 40% the viscosity is 4 whilst a hematocrit value of 60% the viscosity is 8

(Kalbunde 2005). The influence of the hematocrit value on relative viscosity of whole

blood is shown in Figure 2.6.

Figure 2.6 Influence of hematocrit value on the relative viscosity of whole human blood

compared with that of plasma (Klabunde 2005).

The viscosity of human blood increases at lower temperatures, especially those below

15°C (Eckmann et al. 2000). Klabunde (2005) found that a temperature decrease of

20

1°C increases viscosity by approximately 2%. This increase is due to a corresponding

decrease in red blood cell deformability and an increase in plasma viscosity (Kim 2002).

During specialised surgical procedures, such as a cardio pulmonary bypass, the body

temperature of the patient is often lowered to increase the viscosity of the blood

preventing excessive blood flow (Gruber et al. 1999).

2.1.5.2 Variance of Hematocrit values within the Population

Hematocrit value can vary according to age, sex, ethnicity, illness and environment with

normal variation occurring between healthy individuals. Males have a range of 40% to

54%, whereas for females the range is 35% to 40% (Rodak 2002).

It is difficult to obtain a ‘normal range’ or ‘normal value’ for hematology results

obtained from a population. This problem arises due to the variation in health amongst

individuals at the time of blood donation (Dacey and Lewis 1991). It is for this reason

that the terms ‘reference values’ and ‘reference ranges’ are often used in association

with the physiological variables of a sample population. Dacey and Lewis (1991) found

that a number of factors can affect the reference ranges and normal values in

hematology. These include:

• Physical parameters of the sampled subjects, sex, age, build, and ethnic

background

• Sampling conditions

• Specimen collection, timing and storage

• Inherent variation in analytical methods and instrumentation

Donors of blood at a crime scene can differ in hematocrit values from that of the

suggested “healthy or reference range”. Alcoholics, drug and steroid abusers, women

following miscarriages, child birth or abortions, malnourished people and the elderly

can have decreased hematocrit value ranging from 29% to 15%. When the total red

blood cell amount, mass, hemoglobin and hematocrit values decreases by more than

10% a person is diagnosed with anemia (Rodak 2002).

Anemia results in a decrease in oxygen transport due to reduced oxygen carrying

capacity of blood (Birchard 1997) and a corresponding decrease in blood viscosity

(Eckmann et al. 2000). Insufficient red blood cells are present to provide adequate

oxygen transportation to body tissues. Anemia is not a disease, but rather an indicator

21

of a disease somewhere in the body (Marieb 2003). Iron deficiency, autoimmune

diseases, rupturing of the red cell membrane and vitamin deficiencies are all causes of

anemia. Symptoms of anemia include weakness, dyspnea, headache, heart palpitations

and sluggishness, however some suffers will not display any symptoms and often are

unaware of the condition (Dailey 2001). Anemia can also occur as a result of

chemotherapy, during pregnancy and following massive blood loss.

Conversely, raised hematocrit values indicate excessive numbers of red blood cells,

which make the blood thick, increases blood viscosity and impairs circulation (Marieb

2003). These raised values can occur if an individual is dehydrated, in shock, living at

high altitudes, experiencing or about to experience a heart attack, suffering from

hypothermia and following extreme physical activity (Wonder 2001).

Abnormal increases in the number of red blood cells is known as Polycythemia vera

[PV] and can also be experienced by neoplastic blood conditions and prolonged

exposure to high altitudes, where less oxygen is available for cellular intake (McKenzie

1988). In order to maintain the levels of oxygen required for survival, the body

increases red cell production which increases the total amount of red blood cells

compared to plasma [hematocrit value] (Ge Miao 2003). In cases of reduced

atmospheric pressure the body responds by the renal tissue producing the hormone

erythropoietin, which is released into the peripheral blood and stimulates erythropoiesis

[red cell production] in the bone marrow (McKenzie 1988). Although it has been

documented that people living at high altitudes have a higher hematocrit value their

plasma volume is similar to those living at lower altitudes (Claydon et al. 2004).

Hematocrit values also vary with age. Rodak (2002) describes that healthy or normal

hematocrit values are naturally high at birth (45% to 65%), but fluctuate throughout

childhood until about fifteen when the adult average is reached (see Table 2.2).

22

Table 2.2 Hematocrit values (percent) for males and females throughout childhood (Rodak

2002:162).

Age Hematocrit (%)

Male Female Birth to 1 week 45 - 65 45 - 65 1 week to 2 month 37 - 54 37 - 54 2 month to 12 months 31 - 42 31 - 42 12 months to 3 years 33 - 45 33 - 45 3 years to 8 years 32 - 43 32 - 43 8 years to 15 years 33 - 48 33 - 48 15 years to adult 40 - 54 37 – 47

2.1.6 The Use of Human Blood for Experimental Purposes The primary reasons for the use of human blood substitutes, such as ink, paint, glycerol,

dye and animal blood, in past experimental studies are twofold: the inherent dangers of

handling human blood and its availability (Raymond 1997). Blood borne pathogens

such as AIDS and hepatitis are a constant threat to both researchers and crime scene

investigators (Christman 1996; Dailey 2001). As a result, animal blood is most

frequently used for experimental purposes. Validation studies using equine, bovine,

ovine, and porcine blood have been undertaken. The results from these studies indicate

that the viscosity, density and surface tension are relatively similar to human blood,

whilst the “normal range” of hematocrit values differs as shown in Table 2.3 (Raymond

1997; Christman 1996).

Table 2.3 Normal hematocrit values for a variety of mammalian species (Christman 1996).

Species Hematocrit (%)

Male Female Human 42 - 50 40 - 48 Equine 32 - 52 Not Available Bovine 24 - 46 Not Available Porcine 24 - 50 Not Available Ovine 35 - 45 Not Available

Whilst Christman (1996) and Raymond (1997) have demonstrated that for experimental

purposes, animal blood is a suitable alternative to human blood, Wonder (2001) states

that no other substitute behaves like human blood for experimental research purposes.

23

2.1.7 Section Conclusions

This section discussed both the biological and physical properties of blood. Blood is a

complex biological fluid that is essential in maintaining life and to date, no suitable

substitute exists. To truly understand the behaviour of blood at crime scenes, a

comprehensive knowledge of the effect of blood’s underpinning biological and physical

properties is imperative. One of the most important biological properties of blood is its

hematocrit value [amount of red blood cells], but the effect on the formation of

bloodstains and bloodstain pattern has not been sufficiently investigated in the past.

24

2.2 Blood Dynamics

2.2.1 Section Introduction In the past extensive research has been undertaken into aqueous droplet dynamics and in

the early applications of BPA this knowledge was applied to, but not replicated to the

same extent, with blood droplets. As noted in Section 2.1, blood is a complex biological

fluid, which once outside the body, is influenced by a number of complex mechanisms.

The purpose of this section is to provide the reader with a basic understanding of blood

droplet formation, flight characteristics and surface impact dynamics.

2.2.2 Blood Droplet Dynamics in Flight

Raymond et al. (1996) describes five factors which are known to influence the shape of

a liquid droplet:

• surface tension

• hydrostatic pressure

• aerodynamic pressure

• internal circulation

• electric stress

Surface tension has previously been discussed in Section 2.1.4.3; internal circulation

and electrical stress are also believed to have minimal effect on droplet shape

(Pruppacher and Beard 1970; Raymond et al. 1996). Both hydrostatic and

aerodynamic pressures for bloodshed at a crime scene are more complicated than the

aqueous droplet model due to changes in droplet velocity and direction during flight

(Raymond et al. 1996). For both projected and passive blood droplets during flight two

main factors affect trajectory; gravity and air resistance (Carter and Podworthy 1991;

Carter 2003).

It has long been understood that gravity draws everything towards the Earth’s centre

(Wonder 2001). The law of universal gravitation was first published by Newton in

1687 and states that: every point mass attracts every other point mass by a force

pointing along the line intersecting both points. The force is proportional to the

product of the two masses and inversely proportional to the square of the distance

25

between the point masses. Downward acceleration is experienced by all objects due to

the gravitational force exerted upon it by the Earth. The Earth’s force of gravity,

ignoring air resistance, has an approximate value of 9.81m/s² (Serway and Beichner

2000). That means that the acceleration for a free falling blood droplet, falling near the

Earth’s surface, increases by approximately 9.81 meters per second, for every second in

flight. If an object falls in a vacuum the rate of fall is not dependenton the mass of the

object. If that same object falls in air, the rate of fall is dependenton both the mass and

shape of the object [the effect of air resistance] (Wonder 2001).

Air resistance [air friction] is the force that resists the movement of an object due to the

viscosity of air (Carter and Podworthy 1991). Air resistance is related to both the size

and speed of the droplet. An increase in droplet size corresponds to a resulting increase

in droplet mass and momentum when travelling through air. Thus, a larger drop created

on the same trajectory and initiation velocity will travel further because it has increased

momentum and is less affected by air resistance (Reynolds 2008). The direction of

force of air resistance is opposite to the direction of motion of the droplet and changes

as the droplet proceeds along its curved flight path. Given enough time, the droplet

falling through air will reach a constant velocity [terminal velocity]. The droplet will

cease to accelerate as the air resistance is equal to the gravitational pull on the droplet.

According to James et al. (2005) the terminal velocity of 50µL drop of blood is 25.1

ft/sec. Smaller drops will reach terminal velocity quicker than larger drops.

The net result of the forces of gravity and air resistance on the ballistic path of a blood

droplet, projected with some horizontal and vertical velocity, is always represented as

some portion of a parabola [ballistic curve] (Giancoli 1991). Figure 2.7 shows

parabolic arc for a droplet affected by both gravity and air resistance.

26

X

Z

Z0

X0

Parabolic Arc (2 dimensions)

Y

Z

X(x,z,y)

Figure 2.7 Parabolic flight path position instants for a droplet with gravitational force

indicators (blue arrows) and air resistance (pink arrows) (adapted from Carter

2003:8 by Reynolds 2008).

As mentioned in Section 2.1.4.3, surface tension and strong internal cohesive forces

cause a blood droplet to adopt a spherical shape. However, in their early flight history,

blood droplets deviate from this spherical shape due to oscillations (Pizzola et al. 1986;

Pizzola et al. 1986a; Raymond et al. 1996a). An oscillation is cyclical movement

within the mass of the liquid drop resulting in distortion from the spherical shape

(Pizzola et al. 1986; Raymond et al. 1996a; Bevel and Gardner 1997). Figure 2.8 shows

the sphere undergoing an alteration of its length [oblate phase] through to an alteration

of its width [prolate phase] during flight.

27

Figure 2.8 Prolate, spherical and oblate forms of an oscillating blood droplet during flight

(adapted from Raymond et al 1996a: image by Natasha Rogers).

Using high speed photographic recording techniques, Raymond et al. (1996a) were able

obtain width and length measurements of an oscillating blood droplet through its prolate

and oblate flight phases. Both free falling [passive] and projected blood droplets

oscillated strongly during the first few centimeters of flight (Raymond et al. 1996a).

For free falling droplets no detectable oscillation was present after 40cm compared with

100cm for projected blood droplets. A 13% to 22% droplet distortion from the rest

position was observed, with the period of oscillation decreasing as droplet size

decreased. Droplet viscosity is also thought to assist in the dampening of oscillations,

with a blood droplet’s oscillation dampening approximately four times faster than a

water droplet (Bevel and Gardner 1997). Due to the effect of oscillation, an elliptical

blood droplet impacting a perpendicular surface during the prolate oscillation phase

could potentially produce a stain that is similar to that produced by a spherical blood

droplet impacting an angular surface. Subsequently, a blood droplet contacting a

surface too close to release is still likely to be undergoing periodic oscillation and this

may produce a stain of unpredictable shape (Raymond et al. 1996a). Measurement of

these stains will lead to calculation error, therefore the distance from the Region of

Origin [ROO] should be considered when determining appropriateness of bloodstains

for reconstruction measurements.

Prolate Spherical Oblate

28

2.2.3 Blood Droplet Impact Dynamics

Pizzola et al. (1986) were the first to recognise, and specifically describe, a series of

different phases of the dynamic collision of a blood droplet with the solid surface.

Through the use of slow motion photography, Pizzola et al. (1986) formulated the

following description: at contact with the impacted surface, the distortion of the drop is

limited to the lower area but it gradually collapses downwards with respect to the target

surface. The fluid is displaced and forced out forming a rim around the circumference.

The surface tension stops the lateral spreading of the drop with the centre of the stain

depressed. Following the depression the fluid retracts and progresses forward to the

leading edge. If the velocity is sufficiently high, a droplet can separate from the parent

stain creating a satellite spatter.

More recently Bevel and Gardner (2002) separated the impact of a blood droplet on

surface into four distinct phases:

1. Contact and Collapse: The first phase is where a droplet contacts with the

receiving surface and begins to collapse from the bottom up. As the collapse

occurs the blood is forced outwards to the edge of the droplet rim.

2. Displacement: Once the bloodstain has collapsed at the displacement stage, the

majority of the blood has dispersed from the middle of the stain to the boundary.

On the boundary rim are short spines or dimples. These dimples have the

potential to form satellite spatter in the next phase. The area at this stage will

determine the final overall dimensions of the resultant stain. The impact angle

effects the development of dimples. With acute impact angles dimples develop

at the forward stain edge.

3. Dispersion and Expansion: Occurs as the blood is forced into the rims and rises

upwards in an opposite direction of momentum. If the liquid becomes unstable

small droplets of blood may detach and form satellite spatter.

4. Retraction: Due to the surface tension, the droplet will attempt to pull back or

retract from the boundary to a single form. If surface tension is overcome, a

29

portion of the stain will radiate away from the centre causing a spine. If this

liquid breaks away a satellite spatter is formed.

These phases, especially contact and displacement, are dependenton the droplet’s

volume, velocity, height, surface texture of the impact surface and the angle of impact

(Bevel and Gardner 2002). These influencing factors have been shown to be consistent

across most fluids (Yarin 2006). Balthazard et al. (1939) was the first to identify the

relationship between dropping distance, volume and the resultant bloodstain shape.

Droplets produced from lower heights caused circular stains, whilst increasing the

dropping distance resulted in an increased number of spines on the fringe of the stain.

Balthazard et al. (1939) were unable to separate the effects of height and drop volume

on the resultant stain.

Laber (1985) stated that there was no standard volume of a blood droplet generated by a

blood letting event and indicated that when the volume of the droplet increased the

diameter of the resultant stain also increased. MacDonell (1990) proposed that because

different surfaces and circumstances produced blood droplets of differing volumes, the

height from which a droplet originated could not be determined. Pizzola et al. (1996)

and Raymond (1997) supported Laber’s proposition that a standard drop volume was

non existent, rather the volume of any drop is a function of the type, shape and area of

the object from which the droplet falls.

As with dropping height, the velocity of a blood droplet cannot be determined by the

diameter of the resultant stain, as the size of the stain depends on the combined factors

of velocity and drop height (Hulse-Smith et al. 2005). Hulse-Smith et al. (2005)

showed that a 3.7mm diameter droplet released from 30.5cm above the target surface

produces a bloodstain almost identical to a bloodstain produced by a 3.0mm droplet

falling from 121.9cm.

Of all the factors affecting resultant stain shape on a target surface, texture has been

shown to have the greatest influence (Raymond 1997; Eckert and James 1998; Bevel

and Gardner 2002; Hulse-Smith et al. 2005). Wonder (2001) states that surfaces such

as carpet, concrete and clothing produce irregular shaped bloodstains that are spiked

along the outer edge. In contrast, smooth surfaces such a gloss painted walls and floor

tiles produce bloodstains with smooth clearly defined edges. Hulse-Smith et al. (2005)

30

demonstrated that surface roughness promoted fluid instabilities leading to the creation

of spines and that increasing the roughness of a receiving surface reduced both the

resultant stain diameter and number of spines. The decrease in spine number was

proposed to be a result of the analyst’s inability to distinguish individual spines. Hulse-

Smith and Illes (2007) created surface specific equations, using the bloodstain

parameters and the number of spines, to determine impact velocity and droplet volume.

Knock and Davison (2007) stated that it was possible to determine the impact velocity

and position of the blood source for an impact on paper by measuring the stain size and

number of spines, especially for angled surfaces.


Gravity, air resistance and droplet oscillation are all important factors influencing a

blood droplet during flight and the resultant bloodstain shape; therefore, all must be

considered when selecting stains for crime scene reconstructive purposes. Using stain

diameter and number of spines, analytical models have been developed to determine

velocities, drop volume and drop height for particular surfaces. However, the properties

of the receiving surface have been shown to have the greatest effect on resultant stain

diameter and spine production. As time proceeds, an increasing number of papers are

being published concerning droplet flight and impact dynamics but none mention the

potential errors introduced in to the calculations by uncertainties in the biological and

physical properties of blood.

31

2.3 Reconstructive Techniques for Impact Spatter Patterns 2.3.1 Section Introduction Bevel and Gardner (2002) define reconstruction as:

‘...the end purpose of crime scene analysis; it requires not only

consideration of events identified, but whenever possible the sequence of

those events’.

A Bloodstain Pattern Analyst must have the underpinning skills, knowledge and

training to enable the recognition, collection and formal analysis of the evidence (Bevel

and Gardner 2002). This first part of this Section will focus on the foundations that

form the basis of 2-Dimensional [2D] and 3-Dimensional [3D] reconstructions, these

include: pattern identification, calculation of impact angle, bloodstain measuring and

selection. The final part of this section discusses the various reconstructive techniques

available to the Bloodstain Pattern Analyst to determine the blood source origin in

either 2D or 3D space and achieve the objectives of bloodshed reconstruction.

2.3.2 Objectives of Bloodshed Reconstruction

Eckert and James (1998) and Bevel and Gardner (2002) propose that, with careful

examination of an impact spatter pattern the Bloodstain Pattern Analyst may be able to

determine the following:

• The direction a given droplet was travelling at the time of impact

• The angle of impact

• The probable distance from the target from which the droplet originated

• The nature/direction of the force involved in the bloodshed

• The nature of any object used in applying the force

• The approximate number of blows struck during the incident

• The relative position within the scene of the suspect, victim, or other objects

during the incident

• The sequence of multiple events associated with the incident

32

For bloodstain reconstructive purposes it is important for an analyst to determine the

blood source location at the time of pattern creation (Bevel and Gardner 2002). It may

be possible for a bloodstain analyst to determine the blood source location within 2D

[Area of Convergence [AOC]] or 3D [ROO] space.

The correct interpretation of physical evidence is crucial for crime scene reconstruction

(Raymond et al. 2001). Raymond (1997) suggests when attempting to determine a

ROO within a crime scene, the Bloodstain Pattern Analyst may use techniques based on

a number of fundamental assumptions, namely;

• That, just prior to impact on a target surface, the blood droplets are spherical

• That the blood droplets do not coalesce or fragment in flight

• That any spin imparted on the drops does not cause significant trajectory

variation

• That error associated with the measurement of the droplet stains both, from the

measurement system itself, and the decision as to what actually constitutes the

measurement length of any stain is insignificant

• The application of [sin-1 (width/length)] equation for deriving a blood droplet

angle of impact is an accurate representation of the relationship irrespective of

resultant stain parameters

2.3.3 Terminology and Categories of Bloodstains

In order to understand the types of stains and their probable causes, it is useful to

classify stains into categories so that they can be assessed in groups with some degree of

similarity. The use of consistent terminology enables analysts to communicate

effectively around the world. Originally bloodstains and bloodstain patterns were

classified according to the amount of force that created them [high, medium and low]

(Eckert and James 1998; Bevel and Gardner 2002; MacDonnell 2005). More recently a

bloodstain pattern can be identified and classified from the stain’s physical appearance

(size, shape, distribution and location) and the potential mechanism by which the stain

was created (James et al. 2005). Recently, James et al. (2005) developed a taxonomic

key for bloodstain patterns which divides bloodstains into three main categories;

passive, spatter and altered (Figure 2.9).

33

Figure 2.9 Major Bloodstain Pattern Categories (James et al. 2005: 69).

Passive stains are created without any significant outside force other than friction and

gravity; for example, a droplet of blood falling from an exposed wound. Altered

patterns, as the name suggests, have undergone a physical or physiological change, such

as blood and water combination dripping from a washed hand. Spatter patterns are

created when a liquid source of blood is subject to an external force and that force is

sufficient to overcome the physical properties of blood [surface tension and viscosity],

resulting in its distribution through air in droplet form. Spatter can be created by a

variety of mechanisms (James et al. 2005) ranging from an application of force [impact]

to a liquid blood source or liquid blood dripping into blood [satellite stain].

When the Bloodstain Pattern Analyst assesses a bloodstain pattern and it is classified as

spatter, the spatter can further be divided into three categories; secondary, impact and

projected (James et al. 2005) (Figure 2.10). It is the category of impact spatter that is of

most interest for 2D AOC and 3D ROO determinations. Impact patterns result when a

source of liquid blood receives an application of force [impact] resulting in the random

distribution of smaller droplets through the air until their eventual deposition on

adjacent receiving surfaces. The combination of all the individual stains generated by

the same impact or applied force is called a pattern (James et al. 2005). These spatter

patterns will exhibit features that can be used by the analyst to determine the mechanism

of pattern construction, the AOC and/or ROO.

34

Figure 2.10 Bloodstain pattern analysis “Spatter” sub categories (James et al. 2005:108).

2.3.4 Area of Convergence [AOC]

The AOC as defined by Raymond et al. (1997) is the

‘…area to which a bloodstain pattern can be projected on a two-

dimensional surface. This point or area is determined by tracing the

long axis of well-defined bloodstains back to an axis constructed through

the point or Area of Convergence’ (Figure 2.11).

The lines will intersect in an area from which the droplets have originated

demonstrating a 2D geographical location. It is highly unlikely this will be a point, as

no two drops originate from exactly the same point of a blood source (Wonder 2001;

Bevel and Gardner 2002; James et al. 2005).

It is often possible to determine multiple areas of convergence if the blood source

moved between each impact however if the blood source remained in the same position

during repeated force applications those multiple areas of impact will be

indistinguishable. Wonder (2001) states that constructing a accurate AOC is less time

consuming, easier and more accurate for blood / tissue mixes than individual stain

measurements and 3D determination. AOC are always on surfaces whilst the ROO is

located in 3D space (Wonder 2001).

35

Figure 2.11 Two dimensional Area of Convergence [AOC] determination from multiple

bloodstains originating from a single impact (James et al. 2005:218).

2.3.5 Region of Origin [ROO]

The ROO as defined by Raymond et al. (2001) is ‘the three-dimensional area from

which the blood that produced a bloodstain originated. This is determined by

projecting angles of impact from well-defined bloodstains back to an axis constructed

through the point or Area of Convergence. To determine the ROO it is possible to

combine the area convergence with calculated impact angles of selected stains to

determine a ROO in 3D space [X, Y and Z coordinates]. The X coordinate value relates

to the distance away from the spatter bearing surface. The Y coordinate value is vertical

distance from a reference point, usually the spatter bearing surface intersection with the

left wall. The Z coordinate value is the horizontal plane height above a horizontal

reference surface, which is usually the floor (Figure 2.12).

The three techniques for determining ROO are the Tangent Method, String Line Method

or the computer assisted Directional Analysis Method using BackTrack™. Selection of

technique is usually determined by the analyst’s personal preference, availability of

computer assisted methods or limitations associated with the crime scene (James et al.

2005).

36

Figure 2.12 The X, Y and Z coordinate values (image by Natasha Rogers).

2.3.6 Angle of Impact

The acute angle that is formed between the direction of a blood drop and the plane of

the surface it strikes is referred to as the Angle of Impact (Eckert and James 1998;

James et al. 2005) with the trigonometric relationship between the angle at which a

blood droplet impacts a surface and the resultant stain length/width ratio being well

documented (Balthazard et al. 1939; Eckert and James 1998; Bevel and Gardner 2002;

James et al. 2005).

According to MacDonell (1993) it was Florence and Fricon in 1900 who first

investigated the “cause and effect” relationship between angle of impact and stain

length/width ratio. However, the introduction of the theory which became essential in

BPA has been attributed to Balthazard et al. (1939). Their experimentation showed that

a predictable relationship exists between the width to length ratio of a stain and the

angle of impact. MacDonell and Bialosz (1971) also demonstrated the predictable

relationship between the length/width ratio of the resulting bloodstain and the angle at

which the blood droplet struck the static surface.

Z

X

Blood source

Spatter Bearing Surface

Y

37

Figure 2.13 Width to length ratio of a bloodstain equated to a right angle triangle (James et al.

2005:221).

Figure 2.13 illustrates the mathematical relationship between the blood droplet and

resultant bloodstain. Using the properties of the generated right angle triangle the angle

of impact [θ] at B is the same as at point A. The line termed AB [hypotenuse] is equal

to the length of the stain whilst the line BC equates to the width. The 90° angle is

created at point C. The sine of angle θ can then be determined by Equation 2.2.

Sine of angle theta [θ] = opposite / hypotenuse Equation 2.2

But to determine the angle of impact the arcsine of the angle θ is determine by Equation

2.3.

Angle of Impact = arcsine (width / length) Equation 2.3

(MacDonell and Bialousz 1971; Pizzola et al. 1996a; Eckert and James 1998; Carter

2001; Willis et al. 2001; Raymond et al. 2001; Bevel and Gardner 2002; James et al.

2005).

38

The shape of a bloodstain on the impacted surface depends on the angle of impact. The

largest possible angle generated by a droplet surface impact is 90°, which occurs when

the droplet impacts a perpendicular surface. At an impact angle of 90° the shape of the

resultant stain is circular with the length and width measurement being equal (Wonder

2001; James et al. 2005). As the angle of impact becomes more acute the resultant stain

becomes more elongated with a longer measurement along the line of travel [long axis]

(Wonder 2001; James et al. 2005). This long axis, along with the presence of satellite

stains, scallops and spines allows the directionality of a stain to be determined (Bevel

and Gardner 2002). Directionality will be more accurately established when the

resultant stain is more elliptically-shaped on smooth target surface (Bevel and Gardner

2002).

Even though angle of impact can be determined by stain parameters, Pizzola et al.

(1986a) conducted a series of experiments comparing blood droplets that fell onto a

stationary inclined surface with those that fell on a target surface moving horizontally.

They constructed a belt device moving horizontally with an adjustable velocity. Pizzola

et al. (1986a) concluded that the stain parameters produced by a droplet falling

vertically and striking a horizontal surface has the equivalence of stain parameters

produced by a droplet projected onto a moving horizontal surface with adjustable

velocity. Therefore if the target surface is subject to motion it is difficult to establish

true angle of impact, thus the stain may have limited use for reconstructive purposes.

2.3.7 Measuring Bloodstains

One of the most important skills a Bloodstain Pattern Analyst can possess is the ability

to accurately measure the width and length of bloodstains in order to calculate the angle

of impact (Chafe 2003). Before the stain parameters can be measured the analyst must

determine the leading edge of the stain using directionality indicators (James et al.

2005) (Figure 2.14).

39

Figure 2.14 Directionality of bloodstain established with location of the leading and terminal

edges (scale in mm, photograph by Natasha Rogers).

The next step is to determine the maximum width for the bloodstain. Once the

maximum width for the bloodstain has been determined the distance between the centre

point of the bloodstain width line and the leading edge can be found. This distance

between the centre point of the width line and the leading edge is doubled and the

ellipse is superimposed on the bloodstain (Figure 2.15) (Reynolds 2008). Only the

main body of the stain is measured with any scallops, spines or satellites excluded

(Bevel and Gardner 2002; Chafe 2003). The alternative technique of manual

measurement involves the use of electronic calipers [or scaled loupe] with or without

optical assistance (Bevel and Gardner 2002).

Leading Edge

Terminal Edge

40

Figure 2.15 Measurement of the width and length of an elongated bloodstain by fitting a

theoretical ellipse (scale in mm, photograph by Natasha Rogers).

Unfortunately the analyst must judge the best fitting ellipse or manually measure the

length and width and this subjectivity having associated analyst error (Bevel and

Gardner 2002; James et al. 2005). Improper and inaccurate stain measurement can

greatly effect the calculated impact angle. Laturnus (1994) found that the greatest

source of error for manual measurement is the “overestimation” of ellipse length, hence

an “underestimation” of the angle of impact. Bevel and Gardner (2002) suggest that an

error rate for angle of impact calculations of between 5° and 7° is acceptable for

bloodstain reconstruction purposes.

Willis et al. (2001) mathematically determined the potential error rates in the estimation

of angle of impact using a variety of angles of impact 15°, 30°, 45°, 60° and 75°. He

concluded that for reconstructive purposes, stains which impacted the surface at low

angles should be chosen to reduce the potential error rate. These results were supported

by McGuire and Rowe (2004) who stated that stains produced from an impact angle of

80° to 90°, when manually measured, deviated by as much as 19° from the known angle

of impact and therefore should not be used for reconstruction purposes. In the same

study McGuire and Rowe (2004) also disproved a previous hypothesis that stated

impact angles of 10° also deviated considerably from the known impact angle.

41

A recently developed alternative to the manual measurement of bloodstain uses the

Microsoft® Office Excel 2003 Auto Shapes to improve the levels of accuracy and

precision of bloodstain measurement (Reynolds and Raymond 2008). Unlike other

specifically developed computer software programs this program is readily accessible

and requires minimal training (Reynolds and Raymond 2008).

The bloodstain to be measured is first photographed and then imported into a

specifically designed Excel worksheet. The image can be cropped and adjusted

according to the analyst’s requirements. A series of user-friendly macro’s allows grid

lines, a long axis line and ellipse to be placed over the bloodstain (Figure 2.16). The

width to length ratio is established and placed into a tabular master worksheet. The

master worksheet can then be used for statistical analysis or presentation in court should

the specific measurements be required or questioned (Reynolds and Raymond 2008).

Figure 2.16 Measurement of the width and length of a bloodstain using Microsoft® Office

Excel 2003 Auto Shapes (image by Natasha Rogers).

2.3.8 Stain Selection

James et al. (2005) states that there is no ‘magic’ number of bloodstains that should be

selected in order to make a determination of the AOC or ROO. Raymond et al. (2001)

42

suggests at least 12, whilst Carter (2001) advises a greater number of between 18 to 20.

Although analysts cannot agree on the number of stains that should be selected they do

all state that a representative sample of the whole impact spatter pattern should be

obtained by selecting equal numbers of bloodstains from each side of the impact spatter

pattern (Reynolds 2008).

All methods used for determining the ROO using trigonometry, assume that droplet

flight paths are straight lines (James et al. 2005). The determination of the suitability of

a bloodstain for reconstructive purposes can be established by the relative position of

the bloodstain within the pattern and the geometry of the bloodstain itself. Thus for

reconstructive purposes those well formed elongated bloodstains whose flight paths are

approximating a straight line trajectory should be selected (Raymond et al. 2001; Bevel

and Gardner 2002; James et al. 2005). If a clock face was applied to the impact

bloodstain pattern, elongated bloodstains should be selected between the ‘10 and 2

hands of the clock’ (Reynolds 2008). Carter (2001) suggests that stains approaching a

glancing angle approaching 0° [12 on the clock face] should not be used for

reconstructive purposes as it becomes difficult to determine if the blood droplet was

under the influence of gravity and air resistance prior to impacting the receiving surface.

For precision and accuracy of stain measurement, consideration must be given to the

size of the stain, directionality and distance from the ROO. Raymond (1997) stated that

for manual measurement those with impact angles between 30° to 40° where the width

of the stain is > 2.0mm and a length < 8.0mm should be selected. However Reynolds

(2008) concluded when using computer assisted measurement techniques, smaller stains

and those with impact angles <20° can be selected as these bloodstains are approaching

the mathematical theory that the width of the bloodstain is equal to diameter of the

blood droplet.

Bloodstains oscillate during flight with oscillations dampening quickly during flight

(Raymond et al. 1996a). Selecting bloodstains in the outer boundary of the impact

pattern means that the corresponding blood droplets have had an increased flight time

allowing the oscillations to dampen but are being influenced by gravity and thus having

an effect on the resulting bloodstain’s shape.

43

2.3.9 The String Line Method The classic String Line Method as described by MacDonell (1993) and James et al.

(2005), is now deemed outdated by some Bloodstain Pattern Analysts (Laturnus 1998;

Raymond et al. 2001; Carter et al. 2006). The String Line Method is considered

outdated due to its tedious nature, potential analyst error involved in the inaccurate stain

measurement, calculation of impact angle and the actual stringing process when placing

strings along the flight paths (Wonder 2001; Raymond et al. 2001; Carter et al. 2006).

In Western Australia, however the String Line Method is still an applied reconstructive

technique used in the determination of the ROO of an impact spatter pattern. The result

generated from this process provides a good visual representation of the ROO for

presentation in a court of law (Bevel and Gardner 2002).

The String Line Method involves string lines attached to the leading edge of the stain

with the string line extended back along the calculated impact angle, which reflects the

flight path of the selected stains (Knock and Davison 2007). By selecting multiple

stains from various areas of the pattern, the combination of these string lines allows the

ROO to be determined in 3D space [approximate location of the victim] (Maloney et al.

2005). Any convergence of string lines to a single point should be treated as suspicious

(Bevel and Gardner 2002) because the random dispersion of blood droplets caused by

the initial impact mean that no two droplets could have originated from exactly the

same source (Raymond et al. 2001, Bevel and Gardner 2002, Reynolds 2008). The

String Line Method assumes that the flight path of a blood droplet is a straight line not

the parabolic arc that takes into account gravity and air resistance (Knock and Davison

2007). Subsequently, the resultant ROO is often artificially high with the actual

location being at or below the determined area (James et al. 2005).

2.3.10 The Trigonometric [Tangent] Method

When a series of bloodstains have a common AOC the application of the Tangent

Method is often used as an alternative to the manual String Line Method to determine

the Region of Origin (Griffin and Anderson 1993). Originally used as a reconstruction

method for straight line bullet trajectories (Griffin and Anderson 1993; Rowe 2007) the

Tangent Method uses the properties of a right angle triangle to establish the ROO. The

tangent of an angle in a right angle triangle can be defined as the ratio of the side

44

opposite an angle in the triangle to the length of the side adjacent to the angle (Equation

2.4).

Tangent can be defined as Equation 2.4

Tan theta [θ] = opposite adjacent

For reconstruction of an impact pattern a straight line is drawn though the long axis of

the stain with the common AOC then determined for a series of stains. Figure 2.17

represents the application of the right angled triangle to the Tangent Method. The

measurement from the leading edge of the selected stain to the common AOC will give

a length for the adjacent side [AC]. The bloodstain [A] is manually or computer

measured to determine the length and width. The angle of impact is determined using

the basic trigonometric equation [arcsine the measured width to length ratio of each

selected stain]. Using the tangent equation the opposite side measurement can be

obtained [BC], or the distance of a convergence point from a wall, for a vertical surface.

The ROO can be obtained by averaging the distance [BC] for a series of stains.

Figure 2.17 A basic right angled triangle and how this can be used by a Bloodstain Pattern

Analyst to determine the area of origin for a impact pattern on a wall (image by

Natasha Rogers).

Adjacent (AC = distance of stain to convergence site)

Opposite (BC = distance of impact from the wall)

Hypotenuse

B

A (bloodstain)

C

θ

(C = Two dimensional convergence site)

(θ = stain angle of impact)

45

The straight line trajectory nature of the Tangent Method means that the parabolic path

taken by a blood droplet due to the influence of gravity and air resistance is neglected.

As for the String Line Method the calculated blood source height will often be above

the actual blood source height (Bevel and Gardner 2002).

2.3.11 The Computer Assisted [BackTrack™] Method

Computer programs such as BackTrack™ are advocated by Bloodstain Pattern Analysts

because they are quick and can eliminate some of the human error experienced during

the ROO determination (Wonder 2001). BackTrack™ was originally developed by Dr

Alfred Carter of Carleton University and uses digital photographs and directional stain

analysis [ellipse fitting angle of impact] to determine the blood source by giving the

analysts three views of the crime scene [top, side and end] (Carter 2001). The first (top)

view, using virtual strings, shows the intersection of the flight paths of selected blood

droplets, the average of which gives the X and Y positions of the blood source at the

time of impact. A subsequent side view allows the analysis to estimate the height of the

blood source at the time of impact or determine the Z coordinate value (Carter et al.

2006). A validation study completed by Carter et al. (2006) found that the average

difference between the known and calculated values for the X, Y and Z coordinate

values was less than 7cm. This study showed BackTrack™ to be more accurate and less

time consuming than manual String Line Method. But, as with the String Line and

Tangent Methods, the BackTrack™ program also only gives the upper height limit of

the blood source because each of the virtual strings pass directly over the blood source

(Carter 2001). Unfortunately human error is not eliminated with the use of

BackTrack™. Inappropriate stain selection and uncertainty when fitting the ellipse for

impact angle calculations by the inexperienced analyst can still occur (Wonder 2001;

Carter et al. 2006).


The reconstruction of bloodshed events gives both the analyst and the criminal justice

system an insight into physical processes and activities that led to bloodstain pattern

creation. The type of crime scene encountered, analyst personal preference and access

to specific computer programs determines which technique [Tangent Method, String

Line Method, BackTrack™] will be used for reconstruction. When conducting

experimental research to determine the causal affect of a variable the work must be

46

substantially similar to that encountered in the real world. For this reason Chapters 3

and 4 not only provides a detailed examination of the effect of hematocrit value on

individual stain parameters at a variety of impact angles, but also uses the three most

common reconstruction techniques to determine experimental outcomes for

investigators to understand and apply to casework.

47

3. THE EFFECT OF HEMATOCRIT VALUE ON RESULTANT STAIN PARAMETERS

3.1 Experimental Methods 3.1.1 Introduction

Using a passive drop technique (see Section 3.1.5) 30 bloodstains were produced for

each of the 10 different hematocrit values at 4 different angles of impact (see below).

Each stain was manually measured by the author and digitally photographed. The

digitally captured bloodstain was imported into a specifically designed Microsoft®

Office Excel 2003 workbook and measured utilizing the AutoShape function of the

software to computer fit the theoretical ellipse. Using Equation 2.3, the angle of impact,

for each bloodstain, was calculated using both the manual measurement and Microsoft®

Office Excel 2003 Auto Shapes measurement techniques.

3.1.2 Collection and Handling of Blood

In order to reduce the risk of communicable diseases, such as HIV and hepatitis, the

author’s blood was used for all experiments. All blood was used within 21 days of

collection as suggested by Dailey (2001). Venous blood is preferred for most

haematological examinations and is best withdrawn from an antecubital vein by means

of a disposable plastic syringe (Dacie and Lewis 1991). Blood was drawn from the

author by a qualified medical technologist and placed in vials containing the

anticoagulant, Ethylenediamine tetra acetic acid [EDTA]. The sodium and potassium

salts of EDTA, at a concentration of 1.5mg/ml, are powerful anticoagulants and are used

for routine haematological sampling and therefore deemed adequate for this study.

Although EDTA is excess of 2.0mg/ml of blood has been known to cause a significant

decrease in hematocrit value (Dacie and Lewis 1991), the amount of EDTA in the vials

is below 2mg/ml and the hematocrit values were artificially adjusted and tested using an

automated Coulter machine prior to experimentation. MacDonell (1993) and Raymond

(1997) both suggest that EDTA appears to influence the properties of blood, but without

the addition of an anticoagulant the blood would clot and be useless for experimental

purposes. Also, regardless of the addition of the anticoagulant, if blood is allowed to

stand at room temperature it will undergo certain degenerative changes. To retard any

degenerative changes the blood was stored at 4.0°C in the refrigerator prior to

experimental use (Dacie and Lewis 1991; Raymond 1997).

48

Three different methods of measuring hematocrit value currently exist for haematology

testing, the Macro Method [Wintrobes Method], the Micro Method and the Fully

Automated Method using a Coulter machine. The Coulter machine provides an

accurate and reliable means of determining hematocrit value and is currently used by

PathWest for routine haematology work in Western Australia. The author was allowed

to use this machine and all blood drawn was haematologically tested prior to use.

Due to the varying density of the biological components of blood, the cellular

components will begin to settle to the bottom of any container during storage.

Subsequently, blood vials were agitated prior to experimental use to ensure adequate

mixing of the individual components; in order to replicate human body temperature,

prior to experimental use, the blood was placed in a warm water bath heated to

approximately 37.0°C [average human body temperature].

3.1.3 Adjusting Hematocrit Values Ten EDTA vials, each containing approximately 3ml of fresh venous blood, were drawn

from the author’s antecubital vein. One vial was placed on the automated Coulter

machine and the hematocrit value determined [control]. The remaining vials were

centrifuged for ten minutes resulting in the red blood cells settling to the bottom of each

vial. The plasma component [containing water, salts, glucose, fibrinogen, ABO

antibodies, proteins, lipids, waste products and clotting factors] was drawn off using a

Labnet Biopette micropipette and pooled into one large vial. The remaining component

containing the red blood cells [hematocrit value], hemoglobin and ABO antigens, was

drawn off using the same method and pooled in another large vial. Mixing of the buffy

coat containing white blood cells and platelets did occur, but this was unavoidable due

the small fraction of cells lying above the red blood cells becoming disturbed due to the

pipetting technique.

It was determined to achieve the appropriate replication [30 droplets] within the

experimental design, 3ml [standard vial size] of blood was required for each hematocrit

value. Approximate hematocrit values were made up by pipetting a known volume red

blood cells combined with a known volume of plasma into separate vials (Table 3.1).

Due to the viscosity [stickiness] of the red blood cells all the red blood cells were not

removed from the pipette, thus the actual hematocrit values were slightly different from

49

the predicted hematocrit values. For this reason each vial was further tested by the

Coulter machine to determine the specific hematocrit values. A printout of the

haematology data was then obtained.

Table 3.1 Volumes of plasma and red blood cells pipette into labeled vials with the

corresponding predicted hematocrit values versus the actual hematocrit values

used for experimental purposes.

Vial

Number

Pipette Plasma

Volume (ml)

Pipette Red

Blood Cells

Volume (ml)

Predicted

Hematocrit

(%)

Actual

Hematocrit

(%)

1 Normal N/A N/A 36.9

2 0.45 2.55 15 11.2

3 0.75 2.25 25 22.3

4 1.05 1.95 35 28.5

5 1.20 1.80 40 33.7

6 1.50 1.50 50 39.7

7 1.65 1.35 55 46.2

8 1.95 1.05 65 50.2

9 2.10 0.90 70 61.3

10 2.40 0.60 80 68.9

3.1.4 Angle Board

A tilting table with adjustable angle plate was sourced from a local engineering

company and used to determine different angles for the receiving surface. The tilting

table had a solid steel base with an adjustable top plate that was able to move from 0°

[perpendicular to the base plate] to 90° [parallel to the base plate]. The top plate has a

lip to which the receiving surface could be anchored. The required angle was read off

an indicator on the rear of the stand. A Kent 10T high precision [± 0.1°] adjustable set

square was used to manually calibrate the angle plate with each change of known angle.

A Stabila non magnetic spirit level was used to ensure the base plate was level prior to

experimentation and after angle adjustment. The tilting table with adjustable angle plate

was set to 4 different angles of impact 15°, 30°, 45° and 60°. These correspond with the

angles of impact often encountered by an analyst during examination of an impact

spatter pattern. Willis et al. (2001) and McGuire & Rowe (2004) mathematically

50

demonstrated that stains produced from angles of impact >60.0º are unreliable and

therefore should not be used for reconstructive purposes. For this reason impact angles

above 60.0° were not examined.

3.1.5 Experimental Setup

For each of the 10 chosen hematocrit values, 30 blood droplets were deposited onto the

angled surface [smooth, non porous ceramic tiles] at each of the four known angles.

Each droplet had a volume of 18µL and were released from a Labnet BioPette pipette

[2µL to 20µL with a manufactured accuracy of ±0.8%]. The droplets were released

from the pipette by slowly depressing the plunger, allowing the formed droplet to

overcome the physical and chemical properties of blood and fall under the influence of

gravity from the pipette tip. A new clean pipette tip was used for each blood droplet.

The ceramic tiles were cleaned with hot soapy water, rinsed and dried between each

experiment. Each blood droplet underwent a vertical fall of 200cm prior to impacting

the receiving surface. Raymond et al. (1996) found that oscillations dampen after 40cm

for passive drops and 100cm for droplets resulting from an impact. The vertical fall

height of 200cm was chosen to avoid any errors and complications associated with

oscillating blood droplets. A total of 1200 stains were deposited [10 hematocrit values,

4 angles of impacts, 30 replicate blood droplets] to form experimental samples.

3.1.6 Photographic Recording Technique

Following stain deposition each tile was horizontally positioned and allowed to air dry

prior to photographing. Photographing the resultant bloodstains was undertaken using a

Nikon D100 digital camera with a 60mm macro lens. The aperture settings ranged

between f18 to f22, ISO 200 with the speed adjusted according to the amount of

available natural light. The camera was mounted on a secure tripod at an optical axis of

90° to minimise distortion via “camera shake” and allow for timed exposure lengths.

After being photographed each bloodstain image was stored as a high resolution

electronic JPEG file. Prior to photographing a graduated 1mm scale with stain

identification number was placed adjacent to each bloodstain.

51

3.1.7 Manual Measurements of Bloodstains

Once each stain had been photographed it was manually measured by the author using a

pair of electronic callipers [device scaled to 0.1mm] and OptiVisor optical headset [10x

magnification]. The callipers were visually matched to the widest part of the outside

edge of the stain and the stain measurement is read off the electronic display. The

callipers were placed along the long axis of the stain from the tip of the leading edge

until the centre point of the visually determined bloodstain width line. This distance

was read off the electronic display and doubled to gain the total length of the stain

(Chafe 2003). Both the length and width measurements were entered onto a Microsoft®

Office Excel 2003 spreadsheet.

3.1.8 Computer Assisted Bloodstain Measurement Using Microsoft® Office Excel 2003 Auto Shapes

Each bloodstain image was imported into a Microsoft® Office Excel 2003 workbook.

The workbook was specially designed for measuring bloodstains using the Auto Shapes

function (Reynolds and Raymond 2008). The workbook contained 31 worksheets, one

for each imported image and a master sheet containing the automatically linked data for

each of the 30 individual worksheets. Each image was labelled according to its

deposition number, Stain 1 through to Stain 30 for workbook number 1, Stain 31 to 60

for workbook number 2 etc.

Using the picture toolbar each image was adjusted according to individual requirements

and typically involved cropping, resizing, adjusting the contrast and brightness. The

image aspect ratio was locked during all image adjustment. Once the required

adjustment had been achieved each image was saved to the worksheet.

Using the macro automatic functions sets of parallel grid lines and a long axis line were

appropriately positioned on the stain by the author and used to determine the widest part

of the stain and thus the leading edge. An ellipse was placed in the centre of the

positioned grid lines and symmetrically elongated to fit the leading edge. The length

and width of the stain were directly obtained from the ellipse parameters and manually

placed into the appropriate cells. The calculation of the impact angle was automatically

performed using macro functions incorporated in the worksheet. A scale bar was

inserted into the image and lined up with the graduated scale placed adjacent to the stain

52

prior to photographing. The dimensions of the original stain were then obtained and

placed into the worksheet. All this information was automatically transferred to the

master worksheet. Information from each master sheet was then subsequently

combined in a separate Microsoft® Office Excel 2003 workbook for statistical analysis.

3.1.9 Statistical Analysis

For all known impact angles, hematocrit values and stain measurement techniques, the

stain width, stain length, impact angle and difference between known and calculated

impact angle [positive or negative overestimation] was determined. For stains

measured manually statistical analyses compared the width of the stain at known impact

angle of 15º using a one-way Analysis of Variance [ANOVA] and Tukey’s testing [α =

0.05]. The dependent variable was width, the independent variable was hematocrit

value, with each known impact angle being considered separately. Comparisons of

length and calculated impact angle were also made. Bloodstains measured using

Microsoft® Office Excel 2003 Auto Shapes were compared using the same statistical

procedures.

A two-way ANOVA compared the difference between the known and calculated angle

of impact as the dependent variable for the differing hematocrit values and the manual /

Microsoft® Office Excel 2003 Auto Shapes measurement technique. Any interaction

between these independent variables was considered [α = 0.05].

For the manual measurement technique, the response to various hematocrit values for

the four impact angles [α = 0.05] was compared using a two-way ANOVA. Bloodstains

measured using Microsoft® Office Excel 2003 Auto Shapes were compared using the

same statistical procedures.

Two-way ANOVA testing compared the differences between the known and calculated

impact angles for the manual and Microsoft® Office Excel 2003 Auto Shapes

measurement technique, at the four impact angles [significance level = 0.05].

53

3.2 Results

Results obtained for manual and Microsoft® Office Excel 2003 Auto Shapes stain

measurement techniques are shown in Tables 3.2, 3.3 and 3.4. For all known impact

angles it is apparent that there is close agreement between the known and calculated

impact angles irrespective of the hematocrit value.

3.2.1 Impact Angle

At a known impact angle of 15° for both the manual and Microsoft® Office Excel 2003

Auto Shapes measurement techniques, hematocrit value significantly affected the

calculated impact angle [F = 6.85; df = 9, 290; P <0.001, F = 23.33; df = 9, 290; P

<0.001].

The control hematocrit value [36.9%] gave an average calculated impact angle of

15.32° ± 0.49° for manually measured stains and 14.67° ± 0.65° for Microsoft® Office

Excel 2003 Auto Shapes measured stains (Table 3.2 and Figure 3.1). For manually

measured stains the highest average calculated impact angle was achieved for the

control hematocrit value of 36.9% [15.32° ± 0.49°]. However, for Microsoft® Office

Excel 2003 Auto Shapes measured stains the highest average calculated impact angle

was achieved at the highest hematocrit value of 68.9% [16.31° ± 0.88°]. It is of interest

to note that although the average calculated impact angle was deemed to be significant

for both measurement techniques the actual range of averages for manually measured

stains was 1.09° [14.23° ± 0.67° to 15.32° ± 0.49°] and 2.07° for the Microsoft® Office

Excel 2003 Auto Shapes technique [14.24° ± 0.94° to 16.31° ± 0.75°].

At a known impact angle of 30°, hematocrit value had no affect on the calculated

impact angle for manually measured stains [F = 1.51; df = 9, 290; P =0.143]. The

average calculated impact angles ranged from 29.70° ± 1.39° at the lowest hematocrit

value of 11.2% to 30.82° ± 1.27° at a hematocrit value of 50.2%.

At a known impact angle of 30°, hematocrit value significantly affected the calculated

impact angle for Microsoft® Office Excel 2003 Auto Shapes measured stains [F = 16.29;

df = 9,290; P <0.001]. Calculated impact angles were similar for hematocrit values of

28.5%, 11.2%, 39.7%, 33.7%, 22.3%, 36.9% and 61.3%, but different when compared

to the similar calculated impact angles achieved at hematocrit values of 46.2%, 68.9%

54

and 50.2%. Although the calculated impact angle was significantly different the

average calculated impact angles ranged 2.25° from 29.06° ± 0.89° at a hematocrit

value of 28.5% to 31.31° ± 0.90° at a hematocrit value of 50.2%.

For both the manual and Microsoft® Office Excel 2003 Auto Shapes, at a known impact

angle of 45°, hematocrit value significantly affected the calculated impact angle [F =

87.62; df = 9, 290; P <0.001, F = 2.99; df = 9, 290; P <0.01. Although the calculated

impact angle was deemed to be significant for both measurement techniques the actual

range of averages was for manually measured stains 4.77° [40.88° ± 1.86° to 45.65° ±

2.22°] and 1.45° for the Microsoft® Office Excel 2003 Auto Shapes technique [43.76° ±

2.00° to 45.21° ± 1.54°].

For both manual and Microsoft® Office Excel 2003 Auto Shapes, at a known impact

angle of 60°, the hematocrit value significantly affected the calculated impact angle [F =

5.36; df = 9, 290; P <0.001, F = 6.90; df = 9, 290; P <0.001]. The lowest average

calculated impact angle for manually measured stains was at a hematocrit value of

28.5% [55.80° ± 3.30°]. This compared to the highest calculated impact angle at

hematocrit value of 39.7% [60.48° ± 5.19°] for manually measured stains. When

measured using Microsoft® Office Excel 2003 Auto Shapes, the lowest calculated

impact angle occurred at a hematocrit value of 39.7% [58.02° ± 2.35°] whilst the

highest occurred at a hematocrit value of 68.9% [61.44° ± 2.22°].

55

Table 3.2 Shows Manual and Microsoft® Office Excel Auto Shapes (BOLDED) mean calculated impact angle, standard deviation and minimum-maximum range

for bloodstains with different hematocrit values that have fallen on ceramic tiles offset from a vertical at known angle values (n = 30 stains).

Hematocrit Known Angle 11.2 22.3 28.5 33.7 36.9 39.7 46.2 50.2 61.3 68.9

15.0 Manual

Calc Angle 14.23 14.87 14.66 14.70 15.32 14.85 15.26 15.19 14.86 15.12 Std Dev 0.67 0.83 0.78 0.55 0.49 0.71 0.57 0.65 0.75 0.88

Calc Range 12.31-15.66 13.17-17.00 12.73-16.53 13.89-16.19 14.61-16.26 13.69-16.03 14.11-16.83 13.99-16.80 13.39-16.62 13.34-16.85

15.0 Excel


Calc Range 12.29-16.00 13.52-16.03 13.43-15.64 13.31-16.22 13.35-15.95 12.88-15.51 13.27-17.12 13.90-17.89 13.77-18.12 14.61-17.79

30.0 Manual


Calc Range 26.63-33.84 19.42-23.64 25.95-32.48 27.38-32.80 27.21-32.27 28.21-31.77 27.16-32.46 28.54-33.41 26.92-33.12 27.63-34.30

30.0 Excel


Calc Range 27.00-31.54 27.98-31.28 27.51-30.98 27.98-31.76 27.56-31.64 28.27-31.15 28.69-31.32 29.73-32.99 28.02-33.43 29.05-32.33

45.0 Manual


Calc Range 35.80-51.21 39.60-45.47 38.47-51.54 38.10-51.90 39.31-49.61 38.18-48.79 41.14-50.86 37.06-45.39 41.09-50.97 39.98-48.92

45.0 Excel


Calc Range 40.64-47.97 41.56-47.73 42.86-48.54 42.06-48.36 42.05-46.69 41.99-46.80 41.22-47.27 40.47-49.78 42.38-48.30 43.07-49.40

60.0 Manual


Calc Range 52.60-67.14 52.45-66.35 49.35-64.06 52.40-66.70 50.58-64.57 52.58-58.58 53.65-65.63 54.63-65.95 52.92-64.63 50.97-64.45

60.0 Excel


Calc Range 54.03-65.25 54.52-69.04 53.63-66.25 55.70-62.82 53.96-63.15 54.84-63.98 55.34-61.12 54.88-62.45 56.22-65.35 56.55-64.90

56

Comparative Impact Angle Analysis

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

45.0

50.0

55.0

60.0

65.0

70.0

11.2 22.3 28.5 33.7 36.9 39.7 46.2 50.2 61.3 68.9

Hematocrit

Cal

cula

ted

Ang

le o

f Im

pact

15° Manual30° Manual45° Manual60° Manual15° Excel30° Excel45° Excel60° Excel

Figure 3.1 Comparative impact angle for bloodstains created at known impact angles with different hematocrit values, manually measured and measured using

Microsoft® Office Excel Auto Shapes [Error bars represent ±1 Std Dev].

57

3.2.2 Stain Width

For manual and Microsoft® Office Excel 2003 Auto Shapes measurement techniques at

15°, the hematocrit value significantly affected the width of the resultant stain [F =

156.80; df = 9, 290; P <0.001, F = 177.71; df = 9, 290; P <0.001].

The control hematocrit value [36.9%] gave average width measurements of 6.82mm ±

0.20mm and 6.70mm ± 0.24mm for manual and Microsoft® Office Excel 2003 Auto

Shapes measurement techniques, respectively (Table 3.3 and Figure 3.2). For the

manual measurement technique, average stain width decreased by 34% from 7.26mm ±

0.73mm at a hematocrit value of 11.2% to 4.76mm ± 0.44mm at a hematocrit value of

68.9%. This compared to a decrease by 34% from 7.23mm ± 0.74mm at a hematocrit

value 11.2%, to 4.77mm ± 0.43mm at a hematocrit value 68.9% for stains measured

using Microsoft® Office Excel 2003 Auto Shapes.

The widths of bloodstains produced at a known impact angle of 30°, for manual and

Microsoft® Office Excel 2003 Auto Shapes measurement techniques, were affected by

hematocrit value [F = 245.83; df = 9, 290; P <0.001, F = 240.58; df = 9, 290; P

<0.001].

Manual and Microsoft® Office Excel 2003 Auto Shapes measurement techniques

showed width decreases of 34%, for blood with hematocrit values ranging from 11.2%

to 68.9% [average width values fell from 10.50mm ± 0.87mm to 6.96 ± 0.41mm for

manually measured stains and 10.52 ± 0.89mm to 6.99 ± 0.40mm for Microsoft® Office

Excel 2003 Auto Shapes measured stains]. It is interesting to note that average widths

of bloodstains produced by blood within the hematocrit value range of 28.5% to 39.7%,

and measured by both methods, were similar [manually measured 28.5% hematocrit

value = 9.60mm ± 0.49mm; 36.9% hematocrit value = 9.42mm ± 0.56mm; 39.7%

hematocrit value = 9.38mm ± 0.28mm, Microsoft® Office Excel 2003 Auto Shapes

measured 28.5% hematocrit value= 9.64mm ± 0.49mm; 36.9% hematocrit value =

9.52mm ± 0.59mm; 39.7% hematocrit value = 9.42mm ± 0.30mm].

Hematocrit value was shown to affect the width of bloodstains produced at a known

impact angle of 45°, for both manual and Microsoft® Office Excel 2003 Auto Shapes

58

measurement techniques [F = 87.62; df = 9, 290; P <0.001, F = 80.42; df = 9, 290; P

<0.001].

The control hematocrit value [36.9%] gave average widths of 11.33mm ± 0.89mm and

11.12mm ± 0.97mm for manual and Microsoft® Office Excel 2003 Auto Shapes

measurement techniques, respectively. As the hematocrit value increased from 11.2% to

68.9% there was a significant decrease in the width of the resultant bloodstains for both

manual and Microsoft® Office Excel 2003 Auto Shapes measurement techniques. For

manually measured stains a 28% decrease in average width was observed for stains with

a hematocrit value of 11.2% compared with those stains with a hematocrit value of

68.9% [13.01mm ± 0.82mm and 9.37mm ± 0.62mm]. For stains measured using

Microsoft® Office Excel 2003 Auto Shapes a decrease in width by 28% was observed

for stains with a hematocrit value of 11.2% [12.96mm ± 0.85mm] compared with those

stains with a hematocrit value of 68.9% [9.38mm ± 0.70mm].

The width of bloodstains produced at a known impact angle of 60° were affected by

different hematocrit values for both manual and Microsoft® Office Excel 2003 Auto

Shapes measurement techniques [F = 174.78; df = 9, 290; P <0.001, F = 180.11; df =

9, 290; P <0.001].

Average width measurements of stains with a hematocrit value of 11.2% for manual and

Microsoft® Office Excel 2003 Auto Shapes measured stains were 14.59mm ± 0.90mm

and 14.74mm ± 0.85mm respectively. The widths gradually decreased until the average

minimum width was obtained at a hematocrit value of 61.3% for both manually and

Microsoft® Office Excel 2003 Auto Shapes measured stains [9.68 ± 0.41mm and

9.75mm ± 0.46mm]. Similar average width measurements were obtained for hematocrit

values of 36.9%, 39.7% and 46.2% for manually measured stains [11.97mm ± 0.78mm;

11.86mm ± 0.58mm; 11.47mm ± 0.35mm respectively]. Whilst for Microsoft® Office

Excel 2003 Auto Shapes measured stains similar average width measurements were

obtained for hematocrit values of 22.3%, 28.5% and 33.7% [13.12mm ± 0.71mm;

12.80mm ± 0.75mm; 12.66mm ± 0.75mm respectively].

59

Table 3.3 Shows Manual and Microsoft® Office Excel Auto Shapes (BOLDED) mean width (mm), standard deviation and minimum-maximum range for

bloodstains with different hematocrit values that have fallen on ceramic tiles offset from a vertical at known angle values (n = 30 stains).


15.0 Manual

Width 7.26 7.24 6.64 6.21 6.82 6.38 5.88 5.29 4.71 4.76 Std Dev 0.73 0.23 0.36 0.46 0.20 0.36 0.41 0.43 0.30 0.40 Range 5.43-8.41 6.50-7.62 5.69-7.35 4.66-6.74 6.31-7.14 5.48-6.97 5.09-6.68 4.20-5.89 4.13-5.33 3.37-5.68

15.0 Excel


30.0 Manual


30.0 Excel


45.0 Manual


45.0 Excel


60.0 Manual


60.0 Excel


60

Comparative Width Analysis

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

16.00

18.00

11.2 22.3 28.5 33.7 36.9 39.7 46.2 50.2 61.3 68.9

Hematocrit

Wid

th (m

m)


Figure 3.2 Comparative width analysis for bloodstains created at known impact angles with different hematocrit values, manually measured and measured using


61

3.2.3 Stain Length

With a known impact angle of 15° the length of bloodstains were affected by different

hematocrit values for both manual and Microsoft® Office Excel 2003 Auto Shapes


<0.001].

When measured manually a 38% decrease in average stain length was observed when

the blood hematocrit value was increased from 11.2% to 68.9% [29.54mm ± 2.66mm to

18.31mm ± 1.81mm]. This compared to a decrease of 42% in average stain length

observed when the blood hematocrit value was increased from 11.2% to 68.9%

[29.39mm ± 2.25mm to 17.00mm ± 1.58mm] and measured using Microsoft® Office

Excel 2003 Auto Shapes.

Hematocrit value does affect the length of bloodstains produced at a known impact

angle of 30°, for both manual and Microsoft® Office Excel 2003 Auto Shapes


<0.001].

The control, at the hematocrit value of 36.9%, gave average lengths of 18.92mm ±

1.23mm and 19.23mm ± 1.35mm for manual and Microsoft® Office Excel 2003 Auto

Shapes measurement techniques respectively. As hematocrit value increased from

11.2% to 68.9% there was a significant decrease in the length of the resultant

bloodstains. A 35% decrease in average length was observed when bloodstains were

measured manually [hematocrit value 11.2% = 21.20mm ± 1.64mm and 68.9% =

13.87mm ± 1.00mm]. A similar decrease (37%) was observed when bloodstains were

measured using Microsoft® Office Excel 2003 Auto Shapes [hematocrit value 11.2% =

21.66mm ± 1.89mm and 68.9% = 13.73mm ± 0.73mm].

The length of bloodstains produced at a known impact angle of 45° were affected by

different hematocrit value for both manual and Microsoft® Office Excel 2003 Auto

Shapes measurement techniques [F = 9.12; df = 9, 290; P <0.001, F = 80.42; df = 9,

290; P <0.001].

62

Average length measurements at a hematocrit value of 11.2% for manual and

Microsoft® Office Excel 2003 Auto Shapes measured stains were 26.02mm ± 1.64mm

and 18.75mm ± 1.23mm respectively. The lengths gradually decreased until the

average minimum length was obtained at hematocrit value of 61.3% for manually and

Microsoft® Office Excel 2003 Auto Shapes measured stains [17.43 ± 1.12mm and

12.35mm ± 0.95mm]. Similar average length measurements were obtained for

hematocrit values of 36.9%, 39.7% and 33.7% for manually measured stains [22.66mm

± 1.78mm; 21.81mm ± 1.22mm; 21.78mm ± 2.08mm]. Whilst for Microsoft® Office

Excel 2003 Auto Shapes measured stains similar average length measurements were

obtained for 46.2%, 39.7% and 36.9% [14.68mm ± 1.12mm; 15.55mm ± 0.96mm;

15.84mm ± 1.36mm].

At a known impact angle of 60° hematocrit value does affect the length of bloodstains

measured using the both manual and Microsoft® Office Excel 2003 Auto Shapes


<0.001].

As hematocrit value increased the length of the resultant stains decreased. For the

manual measurement technique at a hematocrit value of 11.2% the average stain length

was 16.94mm ± 1.17mm this compared to 11.93mm ± 0.58mm at a hematocrit value

68.9%. For the Microsoft® Office Excel 2003 Auto Shapes measurement technique

average stain length at a hematocrit value of 11.2% was 17.13mm ± 1.11mm this

decrease by 32% to 11.59mm ± 0.61mm at a hematocrit value 68.9%.

63

Table 3.4 Shows Manual and Microsoft® Office Excel Auto Shapes (BOLDED) mean length (mm), standard deviation and minimum-maximum range for

bloodstains with different hematocrit values that have fallen on ceramic tiles offset from a vertical at known angle values (n = 30 stains).


15.0 Manual

Length 29.54 28.24 26.27 24.50 25.84 24.89 22.37 20.19 18.39 18.31 Std Dev 2.66 1.07 1.40 1.92 1.01 1.11 1.84 1.49 1.05 1.81

Calc Range 22.78-33.82 25.28-30.70 23.48-28.20 18.38-27.08 23.66-27.70 21.98-27.22 18.98-25.52 15.40-21.90 16.62-20.34 12.82-21.46

15.0 Excel

Length 29.39 28.55 26.25 24.22 26.49 25.61 22.40 19.97 17.16 17.00 Std Dev 2.25 1.22 1.58 1.94 1.31 1.94 2.28 2.13 1.52 1.58

Calc Range 23.70-33.30 25.92-31.96 22.78-28.69 19.58-27.43 24.30-30.50 20.11-28.91 19.08-26.47 13.22-23.32 14.65-19.77 11.57-20.15

30.0 Manual

Length 21.20 21.88 19.27 20.00 18.92 18.68 17.57 15.20 14.25 13.87 Std Dev 1.64 0.97 1.12 0.80 1.23 0.63 1.21 0.93 0.94 1.00

Calc Range 18.52-24.00 19.42-23.64 17.14-21.80 18.22-21.22 15.46-20.52 17.08-19.88 14.52-19.28 12.78-17.10 12.52-16.12 11.92-16.02

30.0 Excel

Length 21.66 22.28 19.86 20.14 19.23 19.21 17.78 14.91 14.41 13.73 Std Dev 1.89 1.11 1.10 0.73 1.35 0.59 1.08 0.74 0.89 0.73

Calc Range 17.89-24.43 19.50-24.09 17.74-21.67 18.04-21.20 15.79-21.26 17.63-20.09 14.65-19.43 13.34-16.61 11.92-15.72 12.50-15.46

45.0 Manual

Length 26.02 24.78 23.49 21.78 22.66 21.81 20.41 19.36 17.43 18.75 Std Dev 1.64 1.91 2.12 2.08 1.78 1.22 1.36 0.87 1.12 1.23

Calc Range 22.38-27.82 19.96-26.94 18.38-25.78 18.06-26.00 18.60-24.60 18.84-23.54 16.82-22.10 16.76-21.10 14.84-19.70 16.52-22.12

45.0 Excel

Length 18.76 17.18 16.54 15.23 15.84 15.55 14.68 13.75 12.35 13.23 Std Dev 1.24 1.15 1.53 1.44 1.36 0.96 1.12 0.76 0.95 1.02

Calc Range 16.44-20.79 14.81-19.36 12.45-18.69 12.44-17.53 12.41-17.69 13.63-17.19 12.35-16.63 11.72-15.66 9.97-14.27 11.49-15.59

60.0 Manual

Length 16.94 15.76 15.39 14.86 14.01 13.73 13.28 12.55 11.59 11.93 Std Dev 1.17 1.24 1.09 0.78 1.06 1.06 0.61 0.66 0.61 0.58

Calc Range 13.52-18.68 13.46-17.78 13.14-16.78 13.34-16.10 11.86-15.90 11.10-16.08 12.14-14.54 11.20-13.50 10.58-12.82 10.72-12.94

60.0 Excel

Length 17.13 15.46 15.11 14.79 14.13 13.93 13.41 12.72 11.24 11.59 Std Dev 1.11 1.02 0.92 0.58 0.88 0.75 0.42 0.51 0.59 0.61

Calc Range 13.60-18.45 12.79-17.17 12.90-16.52 13.48-15.70 12.28-15.77 11.29-15.00 12.26-14.06 11.50-13.49 10.22-12.55 10.19-12.41

64

Comparative Length Analysis

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

11.20 22.30 28.50 33.70 36.90 39.70 46.20 50.20 61.30 68.90

Hematocrit

Len

gth

(mm

)


Figure 3.3 Comparative length analysis for bloodstains created at known impact angles with different hematocrit values, manually measured and measured using


65

3.2.4 Manual versus Microsoft® Office Excel 2003 Auto Shapes measurement techniques / hematocrit value comparison

The difference between the known and calculated angle of impact for manual and

Microsoft® Office Excel 2003 Auto Shapes stain measurement techniques were affected

by differing blood hematocrit values [F = 33.59; df = 1,2380; P <0.001; F = 7.45; df =

9,2380; P <0.001].

The difference between known and calculated impact angle demonstrated an interaction

between stain measurement technique and hematocrit value [F = 7.87; df = 9, 2380; P

<0.001]. It is of interest to note the greatest difference achieved between the known

and calculated angle of impact was for manually measured stains at 28.5% hematocrit [-

1.75° ± 2.89°] this compared to the least amount of difference that occurred at 50.2%

hematocrit for Microsoft® Office Excel 2003 Auto Shapes stains [0.07° ± 1.80°].

3.2.5 Manual versus Microsoft® Office Excel 2003 Auto Shapes measurement techniques / impact angle comparison

The difference between the known and calculated impact angle was significantly higher

at known angles of 60° and 45° when compared to known angles 15° and 30° [F =

59.16; df = 3, 2392; P <0.001]. At 15° the average difference between the known and

calculated impact angle was -0.03° ± 0.92° this compared to -1.26° ± 3.23° at a known

impact angle of 60°.

For the comparative analysis of stain measurement there is a difference between manual

and Microsoft® Office Excel 2003 Auto Shapes stain measurement techniques [F =

35.31; df = 1, 2392; P <0.001]. The difference between the known and calculated

angle of impact was -0.89° ± 2.67° and -0.37° ± 1.79° for manual and Microsoft®

Office Excel 2003 Auto Shapes respectively. Stain measurement using Microsoft®

Office Excel 2003 Auto Shapes was significantly enhanced from the manual at known

impact angles of both 45° [-2.03° ± 2.91° to -0.28° ± 1.61°]; and 60° [-1.51° ± 3.81° to

-1.01° ± 2.50°].

66

3.2.6 Manual measurement technique – impact angle and hematocrit value comparison

The difference between the known and calculated angle of impact for the manual

measurement technique were affected by differing blood hematocrit value and known

impact angle [F = 6.35; df = 9, 1160; P <0.001; F = 60.03; df = 3, 1160; P <0.001].

For manual measurement the difference between the known and calculated impact angle

was similar at known angles of 60° and 45° [-1.51° ± 3.81° and -2.03° ± 2.91°

respectively], but significantly different when compared to known angles 30° and 15°

[0.08° ± 1.33° and -0.09° ± 0.76° respectively]. The greatest difference between known

and calculated impact angle occurred at hematocrit value 28.5% [-1.75° ± 2.89°] with

the least difference occurring at hematocrit value 46.2% [0.24° ± 1.97°].

The difference between known and calculated impact angle demonstrated an interaction

effect between hematocrit value and the known impact angle [F = 6.22; df = 27, 1160;

P <0.001]. At a known impact angle of 45° and 50.2% hematocrit the difference

between the known and calculated angle of impact was -4.12° ± 1.86° this compared to

0.82° ± 1.27° at a known impact angle of 30° and 50.2% hematocrit. Using the manual

measurement technique 90% of the differences were negative [underestimation of

impact angle] and 10% of differences were positive [overestimation of impact angle].

3.2.7 Microsoft® Office Excel 2003 Auto Shapes measurement technique – impact angle and hematocrit value comparison

For Microsoft® Office Excel 2003 Auto Shapes measured stains the overall difference

between the known and calculated impact angle were affected by both hematocrit value

and known impact angle [F = 25.75; df = 3, 1160; P <0.001; F = 16.72; df = 9, 1160; P

<0.001]. The difference was significantly higher at a known angle of 60° [-1.01° ±

2.50°] and when compared to known angles 15°, 30° and 45° [0.02° ± 1.06°, -0.21° ±

1.13° and -0.28° ± 1.61° respectively].

The difference between the known and calculated impact angle showed an interaction

effect between hematocrit value and the known impact angle [F = 5.02; df = 27, 1160;

P <0.001]. The greatest difference between the known and calculated impact angle

occurred at the highest hematocrit value of 68.9% at 60° [1.44° ± 2.22°]. Using the

67

Microsoft® Office Excel 2003 Auto Shapes measurement technique 70% of differences

were negative [underestimation of impact angle].

3.2.8 General observations

Figure 3.4 shows a series of bloodstains produced using three different hematocrit

values [11.2%, 36.9% and 68.9%] at four known impact angles [15°, 30°, 45° and 60°].

It was observed that bloodstains produced at a lower hematocrit value have a translucent

mottled light red colour, whilst those with higher hematocrit values have more a

uniformed dark red colour [related to the increase in red blood cells].

68

Figure 3.4 Impact angle, hematocrit value and stain shape.

15 Degree 30 Degree 45 Degree 60 Degree

15 Degree 30 Degree 45 Degree 60 Degree

11.2% Hematocrit 36.9% Hematocrit 68.9% Hematocrit

69

3.3 Discussion In actual casework the hematocrit value, and therefore blood viscosity, is unknown. No

testing procedure is currently available that allows for the determination of hematocrit

value or viscosity from a bloodstain. Although the data presented shows that the

hematocrit value appears to significantly effect the calculated impact angle statistically,

all the calculated impact angles were within limits of 5° to 7° as described by Bevel and

Gardner (2002) [Difference range –4.20° to 0.82° for manually measured stains; –1.98

to 1.44 for Microsoft® Office Excel 2003 Auto Shapes measured stains].

For BPA two components of blood are important; plasma and hematocrit value

(Wonder 2001), with the latter having a direct influence on blood viscosity (Raymond

1997; Johnson 1999; Bevel and Gardner 2002; Paut and Bissonette 2002). As

hematocrit values decrease the plasma component of blood increases. This has a

dilution effect, resulting in disproportional decrease in blood viscosity. The viscosity of

blood is important for both blood droplets during flight and upon impact with a

receiving surface. During flight, viscosity helps to dampen oscillations, thus enabling

the droplet to establish a position of equilibrium after the distortion at the propagation

act. Upon impact with a receiving surface, viscosity affects the resultant bloodstain

shape (Raymond 1997). A blood droplet upon impact with a receiving surface

experiences two opposing forces as it makes contact with, and spreads across, the

surface. These forces include those that promote spreading; inertia [density, impact

velocity and volume] and those that resist spread and promoting fluid equilibrium

[surface tension and viscosity] (Hulse-Smith and Illes 2007).

Laber (1985) suggested that the height of origin for a blood droplet could not be

determined from stain diameter if the volume of the droplet was unknown. Laber

(1985) stated that a change in stain diameter is considered a function of a change in

droplet volume and/or impact velocity. This study (Tables 3.3, 3.4 and Figures 3.2, 3.3)

indicated that bloodstain length and width is also a function of blood hematocrit value.

These results indicate that the height of origin for a blood droplet can not be determined

unless droplet volume, impact velocity and the hematocrit value of the resulting

bloodstain is known. Klabunde (2005) determined there is an increase in blood

viscosity with increase in hematocrit value. An increase in viscosity provides a

resistance to spread as the blood droplet contacts and disperses across the impacting

70

surface. It is suggested that the forces that resist spreading increase with an increase in

hematocrit value whilst those that promote spreading potentially remain unchanged.

This study supports Laber (1985) and Willis et al. (2001) who stated that there are

inherent dangers when trying to estimate the distance of fall from the size parameters of

the blood droplet.

The author’s normal blood hematocrit value was 36.9%. For bloodstains created using

an increase from the author’s normal hematocrit value, 50% of experimentally

calculated impact angles were greater than the known impact angle. This is in contrast

to previous studies that have reported an overestimation of ellipse length, leading to an

underestimation of impact angle for manually measuring stains (Laturnus 1994;

Raymond 1997). For bloodstains created using hematocrit values equal to or less than

the authors normal value, only 10% of experimentally calculated impact angles were

greater than the known impact angle. Reynolds (2008) found an overestimation of

impact angle occurred for small bloodstains [≤ 3.0mm long] caused by droplets

impacting a surface obliquely at a known impact angle of 15°. In this study the

overestimation of calculated impact angle was not related to the size of the bloodstains

[all stains ≤9.97mm long], the known impact angle [15° to 60° range], or the stain

measurement technique [manual and Microsoft® Office Excel 2003 Auto Shapes].

As the hematocrit value decreases, the physical appearance of the stain alters. Those

bloodstains produced at a hematocrit value of 11.2% have a translucent mottled

appearance. The visual appearance of the stains at hematocrit value of <36.9% made it

difficult for the analyst to accurately judge the length of the stain or fit the computer

ellipse. The migration of the cells to the terminal edge of the bloodstain may lead to the

overestimation of ellipse length and thus an underestimation of impact angle. No

studies prior to this have reported a significant difference in the experimental and

theoretical expectations based on the visual appearance of the bloodstain. Further

investigation would need to be undertaken using blind trials and multiple bloodstain

analysts.

The United States Supreme Court ruling of Daubert (1993) and Kumho Tyre Company

(1999) have suggested that expert scientific evidence should only be accepted by the

court if a number of criteria can be fulfilled, some of these include; if the hypotheses

within the method can be tested, the method is scientifically reliable with reproducible

71

results and the potential and known error rates are established. Unfortunately, any type

of measurement involves error. Previous studies have indicated that the manual

measurement of bloodstains is relatively inaccurate (Laturnus 1994; Bevel and Gardner

2002). Willis et al. (2001) presented a series of mathematical equations to determine

the error associated with distance of fall and impact angle of bloodstains. They

determined that an impact angle ≤60° can be accurately determined but for anything

>60° the variance increases rapidly as 90° is approached. Raymond (1997) stated that

inaccurate results are inevitable when the impact angle is such that small changes in the

stain length/width ratio make significance difference to the calculated impact angle.

This study showed that bloodstains with known impact angles between 45° and 60°

were measured to within ± 4.20° using both manual and Microsoft® Office Excel 2003

Auto Shapes measurement techniques. This compared to ± 1.31° for bloodstains

measured with known impact angles of 15° and 30°. The results presented for the

passive drop experimentation show that accuracy of the calculated impact angles are all

within the acceptable limits [5° to 7°] as proposed by Bevel and Gardner (2002). The

levels of standard deviation calculated from the data supported the findings by Willis et

al. (2001) with the standard deviations increasing as the known impact angle increased

to 60°. Thus this study demonstrates that measurement precision improved as the

impact angle became more acute.

In the context of an investigation, if the above results are applied to a bloodstain of

angle 15.0°, 100cm from source, the error splay becomes approximately ±2.47cm [Tan

13.69°*100 = 24.36cm, Tan 16.31°*100 = 29.26cm]. For a bloodstain at 60°, 100cm

from the source, the error splay becomes ±33.66cm [Tan 55.80°*100 = 147.14cm, Tan

64.20°*100 = 206.86cm].

Bloodstain measurements must be accurate and reliable. Raymond (1997) concluded

that repeat stain measurement should be carried out for 30° impact angles to improve

accuracy. This study showed that the accuracy and precision of the calculated impact

angle is dependent on the droplet-surface impact angle, with the standard deviation

increasing as the impact angle increased. Subsequently, the data obtained supports the

proposition that to obtain the required accuracy for bloodstain measurement purposes

the impact angle should not be determined by single measurement value. Bloodstain

72

Pattern Analysts should make repeated measurements on the same stain using the same

measurement procedures.

Previous studies have indicated that the width of the stain can be measured accurately,

but the manual measurement of the length is relatively inaccurate (Balthazard et al.

1939; Laturnus 1994; Raymond 1997; Janes 2001; Willis et al. 2001). It has been

recognised that it is common for an analyst to overestimate ellipse length causing an

underestimation of the calculated impact angle (Laturnus 1994; Raymond 1997). This

study showed that for all width measurements standard deviation values were < 1.08,

whilst the standard deviation for length measurements ranged from 0.42 to 2.66. This

supports previous research conducted by Laturnus (1994) and Raymond (1997) who

demonstrated a greater standard deviation for length, as opposed to width,

measurements. However, Laturnus (1994) and Raymond (1997) stated that a major

factor in the analyst’s ability to calculate an accurate angle of impact is the elliptical

shape of the stain, not their ability to judge the stain length. Raymond (1997) suggested

that to accurately determine the impact angle, elliptical stains <30° should be chosen.

To overcome the inaccuracies of manual measurement, the use of digital photography

with computer based ‘ellipse fitting’ measurement methods have been introduced, with

BackTrack™ Images becoming the accepted industry standard (Reynolds 2008). The

use of computer based methods to measure bloodstains to improve accuracy was

validated by Carter (2001). However, the computer program used, BackTrack™

Images, is not readily available to all analysts. In response to the availability issue,

Reynolds (2008) validated the utility of Microsoft® Office Excel 2003 Auto Shapes to

measure bloodstains. Reynolds and Raymond (2008) concluded that Microsoft® Office

Excel 2003 Auto Shapes is an accurate and precise measurement tool for bloodstains,

with this newly developed technique having the potential to replace traditional manual

measurement methods. Although this method doesn’t completely overcome the

subjective overestimation of ellipse length, relative to width, the ellipse visualisation

and symmetrical elongation of the computer generated ellipse minimises

overestimation. The results provide support for the use of Microsoft® Office Excel

2003 Auto Shapes as a replacement for manual measurement, producing calculated

impact angles closer to the known impact angle than the manual measurement

technique. For bloodstains measured using Microsoft® Office Excel 2003 Auto Shapes

the average difference between the known and calculated impact angle was -0.37°.

73

Manually measured bloodstains yielded a difference between the known and calculated

impact angle of -0.89°. These results suggest that the overestimation of ellipse length,

which is commonly seen when using the manual measurement technique, has been

significantly reduced by the use of Microsoft® Office Excel 2003 Auto Shapes.

The results of impact angle calculations at known impact angles of 45° and 60° are of

interest. The results show that for 45° and 60° using Microsoft® Office Excel 2003

Auto Shapes significantly reduces the difference between the known and experimentally

calculated impact angle when compared to the manual measurement technique. Stain

measurement using Microsoft® Office Excel 2003 Auto Shapes was significantly

enhanced from the manual measurement at known impact angles of both 45° [-2.03° to

-0.28°] and 60° [-1.51° to -1.01°]. Subsequently, from a theoretical perspective, a

bloodstain analyst may be able to use stains created at angles >30° to determine a blood

source Region of Origin if the stains were measured using Microsoft® Office Excel

2003 Auto Shapes. Further study would be needed to investigate and validate this

theory.

3.4 Conclusions Blood hematocrit value has been shown to affect the length and width of bloodstains.

Whilst the results from this research show that the affect of hematocrit value on impact

angle calculations is statistically significant. The significance between figures appears

to be due to the mathematical resolving power of the applied statistical test rather than a

divergence from the calculation model used to establish angles of blood droplet impact.

Examination of the known impact angle and experimentally calculated impact angle

from this study demonstrates that the error associated with impact angle calculations for

bloodstains created using a blood hematocrit range of 11.2% to 68.9% falls well within

variation stated in the literature (Laturnus 1994; Bevel and Gardner 2002; James et al.

2005).

74

The present study clearly demonstrates the use of Microsoft® Office Excel 2003 Auto

Shapes to be a reliable method to measure bloodstains. The use of Microsoft® Office

Excel 2003 Auto Shapes allows traceability of electronic data, with the ability of other

analysts or the courts to review and reproduce results. Although the measurement

accuracy was shown to be dependent on surface impact angle, measurements obtained

from impact angles 45° to 60° were still within the industry derived acceptable

variation. The use of Microsoft® Office Excel 2003 Auto Shapes may allow impact

angles of increasing obtuseness to be considered for reconstructive purposes should

limited stains be available for selection.

75

4. THE EFFECT OF HEMATOCRIT VALUES ON IMPACT SPATTER PATTERNS – IMPLICATIONS FOR RECONSTRUCTION

4.1 Experimental Methods

4.1.1 Introduction

This thesis is a two part study examining the effect of blood hematocrit value on

resultant bloodstains and bloodstain patterns. Chapter 3 examined the impact angle

calculations associated with bloodstains created by blood of differing hematocrit values

falling vertically onto inclined surfaces at known impact angles. Chapter 4 examines

the effect of differing blood hematocrit values on generated impact spatter bloodstains

and their relationship on the ability to determine a 2D AOC and 3D ROO for the blood

source.

4.1.2 Collection and Handling of Blood

Approximately 180ml of venous blood was drawn from the author’s antecubital vein by

a qualified medical technologist and placed into 10ml vials containing the anticoagulant

EDTA. After adjusting the hematocrit values [Section 4.1.3] the blood was refrigerated

at 4°C prior to experimentation. The blood was placed in a water, bath heated to 37°C

[body temperature], and inverted to mix the plasma and cellular components prior to

experimentation. All blood was used within 21 days of collection to prevent

degenerative changes (Dailey 2001).

4.1.3 Adjusting Hematocrit Values

The hematocrit value was determined using automated Coulter machine for three 10ml

vials of collected blood. These three vials were used as the control for experimental

purposes. The remaining vials containing the author’s blood were centrifuged for 10

minutes to separate the cellular and plasma components. The cellular and plasma

components were drawn off and separated using a Labnet Biopette micropipette. The

approximate hematocrit values were made up by pipetting a known volume of red blood

cells combined with a known volume of plasma into one large container. Each

container, containing a different hematocrit value, was remixed and tested using the

76

Coulter machine to determine the actual hematocrit value. Once the actual hematocrit

value was determined 10ml was pipetted into three clean vials and labelled with the

actual hematocrit value obtained and the replicate number [1 to 3] (Table 4.1). A

printout of the haematology data was obtained for each actual hematocrit value.

Table 4.1 Predicted hematocrit value versus the actual hematocrit value used for

experimental purposes for plasma and red blood cells.

Container

Number

Number of

replicates

Pipette

Plasma

Volume

(ml)

Pipette Red

Blood Cells

Volume

(ml)

Predicted

Hematocrit

(%)

Actual

Hematocrit

(%)

1 3 25.5 4.5 15 16.7

2 3 21 9 30 30.5

3 (STD) 3 N/A N/A N/A 39.8

4 3 12 18 60 52.9

5 3 7.5 22.5 75 64.8

4.1.4 Experimental Setup

All experiments were carried out at the Western Australia Police Forensic Division in a

specifically designed room for bloodstain pattern trials [width 360cm, length 560cm and

height 267cm]. The room consists of four walls, three that are made of plaster board

and painted with high gloss paint, and one that has glass panels attached to the solid

wall. Only the three painted walls were used for this experiment to limit any error and

uncertainty with different receiving surfaces. For each of the five hematocrit values,

three impact spatter patterns were created.

The bloodstain patterns were created by striking a blood pool of approximately 10ml

volume, which was placed on a clean flat surface, with the blunt end of a claw hammer.

For each pattern the blood source was located at known X, Y, and Z positions of 40cm

from the spatter bearing wall, 180cm from the intersection of the spatter bearing wall

and the right edge and 100cm above the floor. The X, Y, and Z positions were known

to the author prior to reconstruction.

77

From each impact spatter pattern, bloodstains resulting from fast upward moving blood

droplets were selected for measurement and reconstructive purposes. The number of

stains selected was directly dependent on the quality of the stains produced, with the

number of stains selected ranging from seven to 12 for each pattern. Attempts were

made to choose half the stains located to the left of the blood source and half to the right

but this was not always possible due to variations in bloodstains quality.

4.1.5 Stain Measurement

The width and length of each bloodstain was manually measured by the author using a

pair of electronic callipers and OptiVisor optical headset; see Figure 4.1 (refer Section

2.3.7). The angle of impact was then calculated using the relationship between the

width and length of the bloodstain and the angle it strikes a surface (see Equation 2.3).

Each stain was individually photographed using a Nikon D100 digital camera with a

60mm macro lens. The aperture settings were adjusted according to the amount of

available light but the ISO speed remained constant at 200. Due to the location of the

stains and the reflective nature of the receiving surface, the camera was hand held and

the images taken with no flash. The stains were photographed at close range, along

with a graduated 1mm scale, bloodstain identification number, and a vertical plumb line

[for gamma angle measurement]. The bloodstain images were then downloaded and

stored as a high resolution electronic JPEG file.

78

Figure 4.1 Author manually measuring the width and length of a bloodstain using electronic

calipers and OptiVisor headset (image by Brett McCance).

The image produced for each stain was measured using Microsoft® Office Excel 2003

Auto Shapes (refer Section 2.3.7). For each bloodstain pattern a workbook was

compiled containing each individual stain image in a worksheet and master worksheet

for all pattern data. The calculated angle of impact was determined and subsequently

applied to both the Tangent Method and String Line Method.

4.1.6 The Trigonometric [Tangent] Method

For each bloodstain selected; a straight line, using a metal ruler, was drawn through the

major axis of the stain opposite the direction of travel. The area at which all the lines

for a particular pattern intersected on the wall was determined to be the AOC. Using a

hand held Leica Distometer [manufacture accuracy ± 1.5mm] the 2D AOC and the Y

and Z coordinates values for the pattern were determined. The X coordinate value for

each stain was then calculated (refer Figure 2.17). The combined average of each

79

bloodstains X coordinate value provided the overall X coordinate value for the pattern

(Table 4.2).

4.1.7 The String Line Method

For each bloodstain measured using Microsoft® Office Excel 2003 Auto Shapes, a laser

protractor was adjusted to the calculated angle of impact and placed along the major

axis of the bloodstain [pointing towards the AOC]. A red laser beam was emitted by the

protractor onto the floor where the string was to be attached to give the straight line

trajectory of the blood droplet. A string line was then attached from the leading edge of

the stain to each marked position on the floor. The ROO [X, Y and Z coordinate

values] was visually determined by the author from the area where the multiple string

lines intersected (Figure 4.2).

Figure 4.2 Stringing of a impact spatter pattern showing the estimated Region of Origin in

yellow (image by Natasha Rogers).

80

4.1.8 The BackTrack™ Method

The same digital photographs used for both the Tangent Method and String Line

Method were imported into BackTrack™ Images (Figure 4.3). The program was then

used to calculate the glancing [γ] angle and the impact [ά] angle for each stain. This

data was then transferred to BackTrack™ Win to determine the position of the virtual

strings and subsequently the 3D ROO for the blood source.

Figure 4.3 An example of a individual stain, with scale, plumb line and major axis line

photographed for use in both BackTrack™ Images and Microsoft® Office Excel

2003 Auto Shapes (image by Natasha Rogers).

81

4.1.9 Statistical Analysis

For all generated data, the X, Y and Z coordinate values were calculated. The known X,

Y and Z coordinate values were then deducted from the calculated X, Y and Z

coordinate values in order to derive the direction of difference [positive or negative].

The statistical analysis of the data compared the difference between the known and

calculated coordinate values using a two-way Analysis of Variance [ANOVA] and

Tukey’s test [α = 0.05]. The dependent variable was the difference in coordinate value

[positive or negative], with the blood hematocrit value and reconstructive method

[Tangent, String Line and BackTrack™ Images] the two independent variables. The X,

Y and Z coordinates values were considered using separate two-way ANOVA’s. Any

interaction between the two variables was considered [α = 0.05].

A two-way ANOVA and Tukey’s test [α = 0.05] was used to compare the difference

between the known and calculated X coordinate value for the three different stain

measurement techniques [Microsoft® Office Excel 2003 Auto Shapes, Manual and

BackTrack™ Images] applied to the Tangent Method and blood hematocrit value. The

dependent variable was the difference in X coordinate value, and blood hematocrit

value and stain measurement technique [Microsoft® Office Excel 2003 Auto Shapes,

Manual and BackTrack™ Images] the independent variables. Any interaction between

the two variables was considered [α = 0.05].

For impact spatter patterns, statistical analysis compared the difference for all

coordinates values [X, Y and Z] using a one-way ANOVA and Tukey’s test [α = 0.05].

The dependent variable was the difference between the known coordinate value and

calculated coordinate value and the X, Y or Z coordinate value as the independent

variable. A one-way ANOVA and Tukey’s test [α = 0.05] was used to statistically

analyse the difference for all coordinates values [X, Y and Z] [dependent variable] and

the reconstructive method [Tangent, String Line and BackTrack™ Images]

[independent variable]. The final statistical analysis compared the difference for all

coordinates values [X, Y and Z] and blood hematocrit value using a one-way ANOVA.

The dependent variable was the difference between coordinate values with the blood

hematocrit value as the independent variable.

82

4.2 Results

The ROO results obtained for the 15 impact spatter patterns are shown in Tables 4.2 and

4.3. From results shown in Table 4.2 and illustrated in Figures 4.4 - 4.7 it is

immediately apparent that irrespective of reconstructive method applied, blood

hematocrit value has no significant influence on the ability of a Bloodstain Pattern

Analyst to reliably estimate the X, Y and Z blood source ROO.

4.2.1 Comparison of the X Coordinate

No significant difference was noted between the known and calculated X coordinate

values at the different blood hematocrit values [F = 1.55; df = 4, 30; P = 0.213]. The

average difference for the X coordinate values at the lowest hematocrit value of 16.7%

was X = 4.22cm ± 2.86cm [3 pattern average], this was comparative to a difference of X

= 3.56cm ± 2.92cm for the impact spatter patterns created with the highest hematocrit

value of 64.8%. Even though lowest average difference for the X coordinate value was

obtained for patterns created with a 30.5% hematocrit value: X = 1.11cm ± 1.96cm this

was still similar to patterns created with all other hematocrit values. The interaction

between the three different reconstructive techniques and hematocrit value at the X

coordinate value was not significant [F = 0.47; df = 8, 30; P = 0.866].

The ability to determine the X coordinate value was not significantly affected by the

three reconstructive methods [Microsoft® Office Excel 2003 Auto Shapes combined

with Tangent, Microsoft® Office Excel 2003 Auto Shapes combined with the String

Line and BackTrack™ Images] [F = 2.28; df = 2, 30; P = 0.120]. Using the Tangent

Method, the calculated average difference for the X coordinate value was 2.40cm ±

2.59cm. This was similar to the String Line Method average difference of 4.13cm ±

3.11cm and the BackTrack™ Images Method average difference of 2.07cm ± 2.60cm

(Figure 4.4).

83

Table 4.2 Shows Microsoft® Office Excel Auto Shapes, Manual (BRACKETS) and

BackTrack™ (BOLDED) measurement data for bloodstains to determine Region

of Origin using Tangent, String Line and BackTrack™ Methods for Impact

Spatter Patterns 1 to 15.

Pattern Number

(Hematocrit)

Stains

(n)

Coordinate Known

Value (cm)

Tangent Method String Line

Method BackTrack

Method

Cal (cm)

Diff (cm)

Cal (cm)

Diff (cm)

Cal (cm)

Diff (cm)

Pattern 1 (16.7%) 10

X 40 ±2 41 (44) 38 +1 (+4) -2 41 +1 40 0 Y 180 ±2 183 +3 185 +5 169 -11 Z 100 110 +10 105 +5 104 +4

Pattern 2 (16.7%) 7

X 40 ±2 47 (55) 45 +7 (+15) +5 47 +7 46 +6 Y 180 ±2 176 -4 182 +2 179 -1 Z 100 110 +10 108 +8 108 +8

Pattern 3 (16.7%) 9

X 40 ±2 45 (56) 45 +5 (+16) +5

47 +7 44 +4 Y 180 ±2 180 0 183 +3 179 -1 Z 100 110 +10 108 +8 113 +13

Pattern 4 (30.5%) 10

X 40 ±2 42 (42) 41 +2 (+2) +1 45 +5 39 -1 Y 180 ±2 182 +2 190 +10 176 -4 Z 100 106 +6 100 0 114 +14

Pattern 5 (30.5%) 10

X 40 ±2 39 (40) 39 -1 (0) -1 40 0 40 0 Y 180 ±2 174 -6 185 +5 175 -5 Z 100 117 +17 105 +5 112 +12

Pattern 6 (30.5%) 10

X 40 ±2 41 (43) 40 +1 (+3) 0 43 +3 41 +1 Y 180 ±2 182 +2 185 +5 179 -1 Z 100 109 +9 103 +3 108 +8

Pattern 7 (39.8%) 12

X 40 ±2 39 (42) 37 -1 (+2) -3 40 0 37 -3 Y 180 ±2 195 +15 190 +10 178 -2 Z 100 113 +13 115 +15 114 +14

Pattern 8 (39.8%) 12

X 40 ±2 45 (46) 44 +5 (+6) +4 50 +10 42 +2 Y 180 ±2 180 0 190 +10 180 0 Z 100 118 +18 120 +20 121 +21

Pattern 9 (39.8%) 12

X 40 ±2 42 (43) 40 +2 (+3) 0 45 +5 42 +2 Y 180 ±2 180 0 180 0 184 +4 Z 100 121 +21 110 +10 115 +15

Pattern 10 (52.9%) 10

X 40 ±2 44 (47) 43 +4 (+7) +3 45 +5 41 +1 Y 180 ±2 182 +2 183 +3 174 -6 Z 100 102 +2 105 +5 108 +8

Pattern 11 (52.9%) 10

X 40 ±2 45 (47) 43 +5 (+7) +3 44 +4 44 +4 Y 180 ±2 176 -4 182 +2 177 -3 Z 100 110 +10 111 +11 107 +7

Pattern 12 (52.9%) 10

X 40 ±2 41 (43) 41 +1 (+3) +1 40 0 43 +3 Y 180 ±2 179 -1 180 0 179 -1 Z 100 113 +13 100 0 105 +5

Pattern 13 (64.8%) 10

X 40 ±2 39 (37) 39 -1 (-3) -1 45 +5 41 +1 Y 180 ±2 183 +3 192 +12 178 -2 Z 100 115 +15 103 +3 107 +7

Pattern 14 (64.8%) 10

X 40 ±2 41 (42) 42 +1 (+2) +2 42 +2 45 +5 Y 180 ±2 178 -2 190 +10 178 -2 Z 100 113 +13 112 +12 105 +5

Pattern 15 (64.8%) 10

X 40 ±2 45 (41) 46 +5 (+1) +6 48 +8 46 +6 Y 180 ±2 182 +2 190 +10 178 -2 Z 100 117 +17 112 +12 114 +14

84

Impact Patterns: Difference Between the Known and Calculated X Coordinate Using the Tangent, String Line and BackTrack Methods

-4

-2

0

2

4

6

8

10

12

1(16.7)

2(16.7)

3(16.7)

4(30.5)

5(30.5)

6(30.5)

7(39.8)

8(39.8)

9(39.8)

10(52.9)

11(52.9)

12(52.9)

13(64.8)

14(64.8)

15(64.8)

Pattern Number and Hematocrit

Diff

eren

ce (c

m)

Tangent X

Stringline X

Backtrack™ X

Figure 4.4 Difference between the known and calculated X coordinate value using the Tangent, String Line and BackTrack™ Methods to determine the Region of

Origin for 15 impact spatter patterns with differing hematocrit values.

85

Impact Patterns: Difference Between the Known and Calculated Y Coordinate Using the Tangent, String Line and BackTrack Methods

-14-12-10-8-6-4-202468

1012141618

1(16.7)

2(16.7)

3(16.7)

4(30.5)

5(30.5)

6(30.5)

7(39.8)

8(39.8)

9(39.8)

10(52.9)

11(52.9)

12(52.9)

13(64.8)

14(64.8)

15(64.8)


Diff

eren

ce (c

m) Tangent Y

Stringline Y

Backtrack™ Y

Figure 4.5 Difference between the known and calculated Y coordinate value using the Tangent, String Line and BackTrack™ Methods to determine the Region of


86

Impact Patterns: Difference Between the Known and Calculated Z Coordinate Using the Tangent String Line and BackTrack Methods

0

4

8

12

16

20

24

1(16.7)

2(16.7)

3(16.7)

4(30.5)

5(30.5)

6(30.5)

7(39.8)

8(39.8)

9(39.8)

10(52.9)

11(52.9)

12(52.9)

13(64.8)

14(64.8)

15(64.8)


Diff

eren

ce (c

m)

Tangent Z

Stringline Z

Backtrack™ Z

Figure 4.6 Difference between the known and calculated Z coordinate value using the Tangent, String Line and BackTrack™ Methods to determine the Region of


87

Impact Patterns: Difference Between Known and Calculated X Coordinate Using The Tangent Method

-4

-2

0

2

4

6

8

10

12

14

16

18

1 (16.7) 2 (16.7) 3 (16.7) 4 (30.5) 5 (30.5) 6 (30.5) 7 (39.8) 8 (39.8) 9 (39.8) 10(52.9)

11(52.9)

12(52.9)

13(64.8)

14(64.8)

15(64.8)


Diff

eren

ce (c

m)

Microsoft® Office Excel ManualBacktrack™

Figure 4.7 Difference between the known and calculated X coordinate value using the Tangent Method for bloodstains measured using Microsoft® Office Excel

Auto Shapes, Manual and BackTrack™ for 15 impact spatter patterns with differing hematocrit values.

88

4.2.2 Comparison of the Y Coordinate

The difference between the known and calculated Y coordinate was significant between

the blood hematocrit values [F = 2.93; df = 4, 30; P = 0.037]. The average difference

ranged from Y = 4.11cm ± 6.05cm at a hematocrit value of 39.8% to Y = -0.89cm ±

3.02cm for a hematocrit value of 52.9%. Out of the five different hematocrit and X, Y,

Z coordinate values, only two [16.7% and 52.9%] gave a similar negative difference;

both occurred with the Y coordinate value: Y = -0.44cm ± 4.80cm for 16.7%

hematocrit value and Y = -0.89cm ± 3.02cm for 52.9% hematocrit value. The

difference in Y coordinate value was similar for a hematocrit values of 64.8% [Y =

3.22cm ± 5.91cm], 39.8% [Y = 4.11cm ± 6.05cm] and 30.5% [Y = 0.89cm ± 5.35cm].

The interaction between the three different reconstructive techniques and hematocrit

value at the Y coordinate value was not significant [F = 0.72; df = 8, 30; P = 0.670].

The determination of the Y coordinate value was affected by the reconstructive method

[Microsoft® Office Excel 2003 Auto Shapes combined with Tangent, Microsoft® Office

Excel 2003 Auto Shapes combined with the String Line and BackTrack™ Images] [F =

17.28; df = 2, 30; P < 0.001]. When measured by Microsoft® Office Excel 2003 Auto

Shapes and the Tangent Method applied, the calculated average difference for the Y

coordinate value was 0.80cm ± 4.80cm; this result is similar to when BackTrack™

Images was used to determine the Y coordinate value [Y = -2.47cm ± 3.29cm].

However, both of these differed significantly when the Y coordinate value was obtained

using the Microsoft® Office Excel 2003 Auto Shapes combined with the String Line

Method: Y = 5.80cm ± 4.14cm.

When the bloodstains were measured manually, positive Y coordinate values were

obtained for seven of the 15 [47%] impact patterns. For the remaining eight patterns, 3

[20%] recorded an equal Y coordinate value [Patterns 3, 8 and 9], whilst five [33%]

recorded a negative Y coordinate value [Patterns 2, 5, 11, 12 and 14]. The difference

between the actual and calculated Y coordinate ranged from -6cm [Pattern 5] to 15cm

[Pattern 7]. The specific differences between the known and calculated Y coordinate

values using the Tangent Method [combined with Microsoft® Office Excel 2003 Auto

Shapes for stain measurement], Stringline Method [combined with Microsoft® Office

Excel 2003 Auto Shapes for stain measurement], and BackTrack™ Images are shown in

Table 4.2 and illustrated in Figure 4.5.

89

4.2.3 Comparison of the Z Coordinate

The difference between the known and calculated Z coordinate was significantly

different between blood hematocrit values [F = 7.81; df = 4, 30; P < 0.001] and

reconstructive method [Microsoft® Office Excel 2003 Auto Shapes combined with

Tangent, Microsoft® Office Excel 2003 Auto Shapes combined with the String Line and

BackTrack™ Images] [F = 4.60; df = 2, 30; P <0.05]. The average difference for the Z

coordinate was significantly lower for String Line Method [Microsoft® Office Excel

2003 Auto Shapes used for stain measurement] Z = 7.80cm ± 5.62cm when compared to

the Tangent Method Z = 12.27cm ± 4.92cm [Microsoft® Office Excel 2003 Auto Shapes

used for stain measurement]. The difference for the Z coordinate value obtained from

BackTrack™ Images Method [Y = 10.33cm ± 4.79cm] was similar to the String Line

Method [Microsoft® Office Excel 2003 Auto Shapes used for stain measurement] it was

also similar to the Tangent Method [Microsoft® Office Excel 2003 Auto Shapes used for

stain measurement].

The average difference for a hematocrit value of 52.9% was Z = 6.78cm ± 4.24cm. This

was similar to hematocrit values of 30.5% [Z = 8.22cm ± 5.43cm], 16.7% [Z = 8.44cm

± 2.74cm], and 68.8% [Z = 10.89cm ± 4.78cm]. At a blood hematocrit value of 39.8%

[Z = 16.33cm ± 3.87cm] the Z coordinate value was significantly higher than values

obtained for hematocrit values of 52.9%, 30.5% and 16.7%, but similar to hematocrit

value of 68.8% (Figure 4.6). There was no significant interaction between

reconstructive techniques and hematocrit value at the Z coordinate value [F = 0.77; df =

8, 30; P = 0.630].

Although the average difference for the Z coordinate value was as much as 16.33cm ±

3.87cm for patterns created with a blood hematocrit value of 39.8% [three methods and

three pattern average], all the average differences between the known and calculated Z

coordinate values were positive regardless of hematocrit value. For hematocrit values

of 16.7%, 30.5%, 52.9% and 64.8% the Z coordinate value were Z = 8.44cm ± 2.74cm,

Z = 8.22cm ± 5.43cm, Z = 6.78cm ± 4.27cm and Z = 10.89cm ± 4.78cm respectively.

The constant overestimation of the Z coordinate value corresponds to the theoretical

model of using straight lines to replicate blood droplet flight paths.

90

It is of interest to note that although hematocrit value did not significantly affect the

difference between known and calculated coordinate values for X coordinate value, the

greatest difference for the both Y and Z coordinate values were obtained from the

authors control blood hematocrit value of 39.8%: Y = 4.11cm ± 6.05cm and Z =

16.33cm ± 3.87cm (Table 4.2).

4.2.4 Comparison of the Stain Measurement Technique – Tangent Method

Blood hematocrit value did have an affect on the difference between the X coordinate

values when the three different stain measurement techniques [Microsoft® Office Excel

2003 Auto Shapes, Manual and BackTrack™ Images] were applied to the Tangent

Method [F = 4.68; df = 4, 30; P < 0.01]. The greatest average difference for the X

coordinate value was 6.22cm ± 5.89cm for a hematocrit value of 16.7%; compared to

the significantly lower difference for hematocrit values of 39.8%, 64.8% and 30.5%

[2.00cm ± 2.92cm, 1.33cm ± 2.87cm and 0.78cm ± 1.39cm respectively]. There was no

significant interaction between the three different stain measurement techniques

[Microsoft® Office Excel 2003 Auto Shapes, Manual and BackTrack™ Images] and

hematocrit value [F = 1.50; df = 8, 30; P = 0.197].

The three different stain measurement techniques [Microsoft® Office Excel 2003 Auto

Shapes, Manual and BackTrack™ Images] when applied to the Tangent Method did

significantly affect the difference between the known and calculated X coordinate value

[F = 3.80; df = 2, 30; P = 0.034]. The difference obtained for the manual measurement

technique was significantly higher than the BackTrack™ Images measurement

technique, 4.53cm ± 5.15cm and 1.53cm ± 2.75cm respectively. The manual

measurement technique and Microsoft® Office Excel 2003 Auto Shapes measurement

technique were similar, 4.53cm ± 5.15cm and 2.40cm ± 2.59cm respectively.

In 13 of the 15 impact spatter patterns where the bloodstains were measured manually

[87%], positive X coordinate values were obtained this compared with 12 [80%] and

nine [60%] for bloodstains measured using Microsoft® Office Excel 2003 Auto Shapes

and BackTrack™ Images respectively. The specific differences between the known and

calculated X coordinate value using the three different measurement techniques,

combined with the Tangent Method are shown in Table 4.2 and illustrated in Figure 4.7.

91

4.2.5 Comparison of Blood Hematocrit Value

Blood hematocrit value did affect the difference between known and calculated

coordinate values [F = 2.99; df = 4, 130; P = 0.021]. There was a positive average

difference for all of the hematocrit values ranging from 2.96cm ± 4.42cm for a

hematocrit value 52.9% to 7.63cm ± 7.76cm for hematocrit value of 39.8%. The

difference between the known and calculated coordinate values was similar for

hematocrit values of 52.9% [9.96cm ± 4.42cm], 30.5% [3.41cm ± 5.58cm], 16.7%

[4.07cm ± 5.06cm] and 64.8% [5.89cm ± 5.78cm]. However the difference between

coordinate values with hematocrit values of 30.5%, 16.7%, 64.8%, and 39.8% [7.63cm

± 7.76cm] were also similar.

4.2.6 Comparison of the Coordinate Value

The Z coordinate was significantly different when compared with the X and Y

coordinate values [F = 45.76; df = 2, 132; P <0.001]. The average difference between

the known and calculated X value was 2.87cm ± 2.87cm and the Y value 1.38 ±

5.30cm. There was a significant increase from difference for both the X, and Y value to

the Z value of 10.13cm ± 5.34cm.

4.2.7 Comparison of Reconstructive Technique

Overall the reconstructive technique [Microsoft® Office Excel 2003 Auto Shapes

combined with Tangent, Microsoft® Office Excel 2003 Auto Shapes combined with the

String Line and BackTrack™ Images] had no affect on the average difference between

the known and calculated coordinate values [X, Y and Z] [F = 2.28; df = 2, 132; P =

0.106]. The average differences were 5.16cm ± 6.59cm for Microsoft® Office Excel

2003 Auto Shapes combined with Tangent, 5.91cm ± 4.57cm for Microsoft® Office

Excel 2003 Auto Shapes combined with String Line Method and 3.31cm ± 6.45cm for

BackTrack™ Images Method. Although the differences up to 21cm [Pattern 8

BackTrack™ Images Z coordinate value and Pattern 9 Tangent Method Z coordinate

value] were observed between the known and calculated coordinate values, Region of

Origin similarity is evident between the Tangent, String Line and BackTrack™ Images

Methods.

92

Average manual, Microsoft® Office Excel 2003 Auto Shapes and BackTrack™ Images

measurement data for these bloodstains is shown in Table 4.3. Close measurement

agreement is evident between the manual, Microsoft® Office Excel 2003 Auto Shapes

and BackTrack™ Images measurement methods. When manually measured the average

calculated ellipse width [n = 152] was 1.20mm [range 0.94mm to 1.52mm], average

calculated ellipse length [n =152] was 3.69 [range 2.87mm to 4.80mm] and the average

calculated impact angle over the 15 patterns was 19.80° [range 15.91° to 24.16°]. When

measured using Microsoft® Office Excel 2003 Auto Shapes the average calculated

ellipse width [n=152] was 1.21mm [range 0.94mm to 1.54mm], average calculated

ellipse length 3.81 [range 2.96mm to 5.00mm] and the average calculated impact angle

for the 15 patterns was 18.70° [range 15.82° to 21.27°]. When measured using

BackTrack™ Images the average calculated ellipse width [n=152] was 1.18mm [range

0.93mm to 1.51mm], average calculated ellipse length [n=152] was 3.78 [range 2.90mm

to 4.98mm] and the average calculated angle of impact for the 15 pattern was 18.26°

[range 15.43° to 21.73°].

Figures 4.8 to 4.12 show Impact Spatter Pattern 2 created with a blood source

hematocrit value of 16.7%. Figures 4.13 to 4.20 show Impact Spatter Pattern 15 created

with a blood source hematocrit value of 64.8%. In order to give an indication of a

spatial context for the various experimental treatments conducted, comparative X, Y

and Z coordinate measurement results for the actual blood source and the

experimentally derived values using the Tangent Method [combined with the

Microsoft® Office Excel 2003 Auto Shapes measurement technique], String Line

Method [combined with the Microsoft® Office Excel 2003 Auto Shapes measurement

technique] and BackTrack™ Images Method are indicated.

93

Table 4.3 Shows Manual, Microsoft® Office Excel Auto Shapes (ITALICS), BackTrack™ (BOLDED) measurement data for bloodstains for Impact Spatter Patterns

1 to 15.

Stains Bloodstain Width Bloodstain Length Impact Angle Calculations (n) Range (mm) Average (mm) Range (mm) Average (mm) Range Average

Pattern 1 (16.7) 10

0.84 – 1.68 1.10 2.56 – 6.38 3.42 15.27 – 23.48 19.23 0.82 – 1.74 1.08 2.56 – 6.04 3.55 13.10 – 21.30 18.00 0.83 – 1.69 1.05 2.47 – 6.31 3.64 13.80 – 19.70 16.96

Pattern 2 (16.7) 7

1.22 – 2.15 1.62 3.32 – 4.58 3.68 21.56 – 31.77 26.07 1.24 – 2.17 1.62 3.22 – 5.43 4.11 20.50 – 25.50 23.11 1.24 – 2.25 1.61 3.36 – 5.43 4.28 19.60 – 24.40 22.01

Pattern 3 (16.7) 9

1.14 – 1.62 1.35 2.84 – 3.74 3.32 21.64 – 32.44 24.27 1.09 – 1.58 1.33 2.98 – 4.53 3.84 17.70 – 26.10 20.47 1.04 – 1.58 1.32 3.03 – 4.65 3.82 16.70 – 25.60 20.49

Pattern 4 (30.5) 10

0.82 – 1.57 1.26 3.34 – 5.86 4.23 13.11 – 23.50 17.54 0.90 – 1.65 1.27 3.23 – 5.71 4.14 15.30 – 20.10 17.77 0.80 – 1.60 1.23 3.30 – 5.50 4.13 14.20 – 21.20 17.44

Pattern 5 (30.5) 10

0.95 – 1.40 1.17 2.94 – 4.72 3.79 14.34 – 21.97 18.30 1.04 – 1.42 1.19 3.24 – 5.00 3.93 15.10 – 19.90 17.75 1.06 – 1.39 1.18 3.05 – 4.88 3.89 14.90 – 20.60 17.92

Pattern 6 (30.5) 10

0.97 – 1.20 1.12 2.90 – 4.90 3.62 14.06 – 23.58 18.47 1.00 – 1.29 1.15 2.99 – 4.39 3.77 15.60 – 21.30 17.92 0.97 – 1.24 1.10 2.96 – 4.35 3.66 16.00 – 22.30 17.62

Pattern 7 (39.8) 12

0.73 – 1.34 0.89 2.34 – 3.44 2.77 15.68 – 22.93 18.73 0.67 – 1.29 0.85 2.27 – 4.16 2.85 15.60 – 18.30 17.34 0.60 – 1.30 0.82 2.20 – 4.50 2.89 14.30 – 18.60 16.68

Pattern 8 (39.8) 12

0.97 – 1.45 1.22 2.86 – 5.08 3.65 14.87 – 26.36 19.94 0.99 – 1.43 1.22 2.84 – 5.40 3.68 14.80 – 23.90 19.67 0.96 – 1.37 1.17 2.90 – 5.17 3.60 14.50 – 26.50 19.36

Pattern 9 (39.8) 12

0.87 – 1.48 1.17 3.00 – 4.74 3.78 15.47 – 21.05 18.10 0.89 – 1.42 1.18 2.78 – 4.64 3.89 15.90 – 21.80 17.84 0.85 – 1.47 1.16 2.71 – 4.89 3.94 14.90 – 21.40 17.23

Pattern 10 (52.9) 10

0.94 – 1.22 1.08 2.40 – 4.64 3.43 15.24 – 23.06 18.70 0.90 – 1.29 1.05 2.85 – 4.34 3.52 15.00 – 18.90 17.31 0.87 – 1.23 1.02 2.66 – 4.55 3.48 13.30 – 19.90 17.27

94

Stains Bloodstain Width Bloodstain Length Impact Angle Calculations

(n) Range (mm) Average (mm) Range (mm) Average (mm) Range Average

Pattern 11 (52.9) 10

0.92 – 1.49 1.17 2.62 – 3.94 3.39 16.13 – 26.28 20.44 0.95 – 1.52 1.19 2.77 – 4.28 3.51 16.20 – 24.40 19.92 0.90 – 1.50 1.15 3.00 – 4.23 3.49 16.20 – 22.10 19.02

Pattern 12 (52.9) 10

1.03 – 1.84 1.33 2.84 – 5.50 4.04 16.78 – 22.10 19.27 0.96 – 1.82 1.28 2.93 – 5.72 4.06 15.90 – 20.30 18.39 0.94 – 1.74 1.25 2.95 – 5.61 3.96 16.40 – 20.10 18.44

Pattern 13 (64.8) 10

0.81 – 1.28 1.04 2.96 – 4.18 3.71 14.30 – 21.78 16.36 0.83 – 1.21 1.02 2.74 – 4.37 3.56 14.70 – 19.50 16.87 0.83 – 1.17 1.00 2.58 – 3.98 3.41 15.60 – 18.70 17.08

Pattern 14 (64.8) 10

0.97 – 1.58 1.32 3.12 – 5.36 4.43 15.35 – 21.83 17.51 1.04 – 1.83 1.38 3.60 – 6.06 4.72 15.80 – 22.10 17.14 0.99 – 1.54 1.34 3.37 – 5.28 4.50 15.40 -21.00 17.34

Pattern 15 (64.8) 10

0.92 – 1.45 1.18 3.00 – 4.96 4.04 14.86 – 20.23 17.11 1.07 – 1.52 1.29 3.35 – 4.89 4.06 16.10 – 22.40 18.76 1.02 – 1.54 1.28 2.96 – 5.34 3.99 15.60 – 23.90 18.98

0.94 – 1.52 mm 1.20 mm 2.87 – 4.80 mm 3.69 mm 15.91° – 24.16° 19.80° 0.96 – 1.54 mm 1.21 mm 2.96 – 5.00 mm 3.81 mm 15.82° – 21.27° 18.70° 0.93 – 1.51 mm 1.18 mm 2.90 – 4.98 mm 3.78 mm 15.43° – 21.73° 18.26°

95

Figure 4.8 Impact Spatter Pattern 2 (16.7 Hematocrit) – actual blood source Z value indicated.

Figure 4.9 Impact Spatter Pattern 2 (16.7 Hematocrit) – Comparison of experimentally derived Z coordinate values with actual blood source Z coordinate value.

Z Actual 100cm

Z Actual 100cm Z Tangent 110cm

Z Stringline 108cm Z BackTrack™ 108cm

96

Figure 4.10 Impact Spatter Pattern 2 (16.7 Hematocrit) – Comparison of experimentally

derived X coordinate values with actual blood source X coordinate value.


derived Y coordinate values with actual blood source Y coordinate value.

X Actual 40cm X Tangent 47cm

X Stringline 47cm X BackTrack™ 46cm

Y Actual 180cm Y Tangent 176cm

Y Stringline 182cm Y BackTrack™ 179cm

97

Figure 4.12 Impact Spatter Pattern 2 (16.7 Hematocrit) – wooden blood source support positioned as to indicate the actual blood source location top of blood.

98

Figure 4.13 Impact Spatter Pattern 15 (64.8 Hematocrit) – actual blood source Z coordinate

value indicated.


derived Z coordinate values with actual blood source Z coordinate value.

Z Actual 100cm

Z Actual 100cm Z Tangent 117cm

Z Stringline 112cm Z BackTrack™ 114cm

99

Figure 4.15 Impact Spatter Pattern 15 (64.8 Hematocrit) – Comparison of experimentally derived X coordinate values with actual blood source X coordinate value.

Figure 4.16 Impact Spatter Pattern 15 (64.8 Hematocrit) – wooden blood source support positioned as to indicate the actual blood source location top of block.

X Actual 40cm X Tangent 45cm

X Stringline 48cm X BackTrack™ 46cm

100

Figure 4.17 Impact Spatter Pattern 15 (64.8 Hematocrit) – Comparison of experimentally derived Y coordinate values with actual blood source Y coordinate value.

Figure 4.18 Top view 2D representation of Impact Spatter Pattern 15 (64.8 Hematocrit) using BackTrack™. The red cross indicates the X and Y coordinates.

Y Actual 180cm Y Tangent 182cm

Y Stringline 190cm Y BackTrack™ 178cm

101

Figure 4.19 Side view 2D representation of Impact Spatter Pattern 15 (64.8 Hematocrit) using BackTrack™. The red cross indicates the X and Z coordinates.

Figure 4.20 End view 2D representation of Impact Spatter Pattern 15 (64.8 Hematocrit) using BackTrack™. The red cross indicates the Y and Z coordinates.

102

4.3 Discussion

The results demonstrate a significant difference between the determination of X, Y and

Z coordinate values for the varying blood hematocrit values. However, the calculated

coordinate values are all within the acceptable industry limits as described by Carter et

al. (2006). The reported statistical differences appears to be a function of the resolving

power of the applied mathematics. Subsequently, hematocrit value of blood does not

influence the analysts’ ability to reliably determine the ROO for a blood source within

3D space. Further, the impact spatter patterns support the results obtained for the

passive drop experiments (see Section 3.2). Although hematocrit value was

demonstrated to affect the width and length of the resultant bloodstain, a proportional

relationship appears to exist such that hematocrit value does not affect the width to

length ratio and thus the reliability of the calculated impact angle (see Section 3).

The formation of an impact spatter pattern is influenced by a number of factors

including; velocity of impacting force, directionality of applied force, dimensions of the

wound providing the blood source, surface texture and physical obstructions (James et

al. 2005). It is of interest to note it was difficult to produce bloodstain impact patterns

with a blood hematocrit value of 16.7%. After the application of the impact force to the

blood source with a 16.7% hematocrit value it was evident that the bloodstains were not

deposited as high in the vertical direction on the receiving surface. Also, the individual

bloodstains were generally larger in diameter than bloodstains of impact patterns

produced with a higher blood hematocrit value. The observed difference in bloodstain

size for the impact patterns is supported by studies undertaken in Chapter Four which

showed that hematocrit value decreased, both stain width and length increased. These

results suggest that for impact spatter patterns the distribution and representative size of

bloodstains are also a function of the hematocrit value and not just the levels of applied

force.

For each of the 15 impact patterns, irrespective of the reconstructive technique used, the

calculated Z coordinate value was equal to or greater than the known Z coordinate

value. The calculated Z coordinate value [height of the blood source from the ground]

provides an upper limit for the blood source. All bloodstain reconstructive techniques

assume that the blood droplet travels in a straight line trajectory but it has been

determined that a blood droplet actually follows a parabolic flight path due to the

103

influence of gravity and air resistance (Carter 2001; Carter et al. 2005; James et al. 2005

Carter et al. 2006). The blood droplet’s actual flight path cannot be calculated because

the size and speed of the blood droplets is unknown. Therefore, by using of straight line

trigonometry to replicate droplet flight paths the calculated Z coordinate value will

always be higher than the actual blood source value (Carter 2001; Carter et al. 2006).

For the impact spatter patterns a maximum difference between the known coordinate

value and experimentally calculated coordinate value occurred on the Z coordinate

[21cm] (Table 4.2). The average difference between the known and calculated X

coordinate value is 2.87cm, 1.38cm for the Y coordinate value, and 10.13cm for the Z

value. These X, Y, and Z values are less than the radius of a human head, a comparison

used by Carter et al. (2006). The results obtained for this experiment support Carter et

al. (2006) who stated that when estimating the intersection of strings a range of 10cm to

20cm is typical and even with this range it is still adequate to allow the interpretation of

events that may have led to the pattern deposition [the position of the victim; laying,

sitting or standing]. Carter et al. (2006) had similar results when using BackTrack™

alone to determine ROO of a blood source.

For impact spatter patterns found at an actual crime scene the size of the blood source

[wound] will have a direct impact on the analysts ability to determine the location of the

blood source. A blood droplet could originate from any point within the wound plus

any area on which blood has been deposited (James et al. 2005). For this experiment

the static blood source was stated with known X and Y coordinates and a ±2cm level of

accuracy. With the known values having a ±2cm level of accuracy it can therefore be

assumed that the calculated X and Y coordinates will also have ±2cm level of variation

without taking into account any other potential sources of reconstructive error.

When the Tangent Method [combined with Microsoft® Office Excel 2003 Auto Shapes]

was used to determine the Region of Origin of the blood source, equal or positive X

coordinate values were obtained in 10 out of the 15 impact patterns [67%]. For the

String Line Method [combined with Microsoft® Office Excel 2003 Auto Shapes] 15 out

of 15 [100%] equal or positive X coordinate values were calculated. When the

BackTrack™ Images Method was used to determine the Region of Origin, equal or

positive X coordinate values were obtained for two out of 15 impact patterns [13%]. A

positive X coordinate value indicates that the calculated blood source will be further

104

away from blood bearing surface than the actual X value (Reynolds 2008). The

overestimation of the location of the blood source indicates an overestimation in

calculated impact angles for the selected bloodstains [underestimation of ellipse length,

relative to width]. However, an underestimation of the blood source location indicates

an underestimation in calculated impact angles. James et al. (2005) suggest that a 10%

difference in the X coordinate can be explained by a systematic underestimation of

ellipse length with the remaining difference being attributed to either random error or

inappropriate stain selection.

When applying the Tangent Method, the measurement of bloodstains using computer

programs [Microsoft® Office Excel 2003 Auto Shapes and BackTrack™ Images] is

more accurate than measuring the stains manually. However, for reconstructive

purposes using either the Tangent Method or String Line Method is as accurate as using

the computer program, BackTrack™ Images. These results support Carter et al. (2006)

who determined that even though it was expected that the computer program

BackTrack™ Images would be more accurate than the manual String Line Method, the

results obtained were actually not significant. Therefore the uncertainties in the

reconstructed path of a blood droplet can obviously be minimised through the use of the

best measurement technique available [Microsoft® Office Excel 2003 Auto Shapes or

BackTrack™ Images] with a Bloodstain Pattern Analyst having the ability to choose the

reconstructive technique that suits a particular bloodshed scene, based on both the

physical factors of the scene and the analyst’s ability to access the computer programs

without compromising accuracy.

105

4.4 Conclusions The findings of the present thesis provide an insight into the effect of one specific

biological property of blood [hematocrit percent of blood] on the reconstruction of

bloodshed events.

The main objectives of this study were:

(i) To determine the effect of hematocrit value on the angle of impact

calculation theory using single drop experimentation (Chapter 3).

(ii) To examine any error associated with the calculation of angle of impact for

bloodstains generated with different blood hematocrit values using both

manual and computer assisted measurement techniques (Chapter3).

(iii) To determine if the ability to predict the ‘Region of Origin’ of the blood

source is influenced by hematocrit value. This will be conducted using

three different industry accepted reconstruction methods: the String Line

Method [combined with Microsoft® Office Excel 2003 Auto Shapes], the

Tangent Method [combined with Microsoft® Office Excel 2003 Auto

Shapes] and computer assisted Directional Analysis Method [BackTrackTM

Images] (Chapter 4).

Subsequently, the main conclusion of this thesis is:

(i) Donor blood hematocrit values have no effect on the reliable determination

of the Region of Origin of the blood source.

Additional thesis conclusions are:

(ii) The computer fitting of a theoretical ellipse for bloodstain measurement

purposes is more accurate than manual measurement.

(iii) All three reconstructive techniques [The Tangent, The String Line and

BackTrack™ Images] are comparable and reliable blood source Region of

Origin determination methods.

106

5. Future Directions

The Use of the Three Dimensional Scanner for Bloodstain Impact Pattern

Reconstruction: The Western Australia Police Forensic Division does not currently use

BackTrack™ Images for the virtual reconstruction analysis of bloodshed events.

Although results presented in this thesis suggest that the String Line Method is reliable

when compared to BackTrack™ Images, a question has arisen from this study; are there

any other computer assisted methods available for 3D reconstruction of bloodshed

events? With the introduction of 3D scanners for the forensic investigation and

examination of crime scenes it has been noted that bloodstains and bloodstain patterns

can be observed on the computer generated image. Can the 3D scanner be used to

determine the 3D Region of Origin and is it a valid reconstructive technique when

compared against the current industry accepted methods.

Selection of Bloodstains for Reconstructive Purposes: When using Microsoft® Office

Excel 2003 Auto Shapes to fit an ellipse to a bloodstain and calculate the impact angle,

it was noted that accurate results were obtained for bloodstains created at angles <30°.

As such, bloodstains <30° may be used for 3D Region of Origin determination. Further

studies are required relating to the accuracy and precision of impact angles <30° to

determine the 3D Region of Origin.

Determining the Error Range for each Reconstructive Technique: This thesis

mentioned that industry accepted error rates occur for each reconstructive technique. In

order to reliably present the Region of Origin results in a court of law research into the

source of these errors is required. Is the error a combination of blood sheeting

[movement in the vertical direction of the blood volume before detachment of the blood

droplet], measurement error, bloodstain selection, and/or impact velocity?

107

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