A Long Term Wearable Electrocardiogram (ECG)

Measurement System

by

Margaret (Maggie) K. Delano

S.B., E.E., M.I.T. (2010)

Submitted to the Department of Electrical Engineering and ComputerScience

in partial fulfillment of the requirements for the degree of

Masters of Engineering in Electrical Engineering and ComputerScience

at the

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

June 2012

© Margaret (Maggie) K. Delano, MMXII. All rights reserved.

The author hereby grants to MIT permission to reproduce anddistribute publicly paper and electronic copies of this thesis document

in whole or in part in any medium now known or hereafter created.

Author . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Department of Electrical Engineering and Computer Science

May 21, 2012

Certified by. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Dr. Charles G. Sodini

Clarence J. LeBel ProfessorThesis Supervisor

Accepted by . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Prof. Dennis M. Freeman

Chairman, Masters of Engineering Thesis Committee

2

A Long Term Wearable Electrocardiogram (ECG)

Measurement System

by

Margaret (Maggie) K. Delano

Submitted to the Department of Electrical Engineering and Computer Scienceon May 21, 2012, in partial fulfillment of the

requirements for the degree ofMasters of Engineering in Electrical Engineering and Computer Science

Abstract

In this thesis, a low-power, wearable monitoring system was developed from discreteelectronic components and custom PCBs. The device was designed to maximizecomfort and minimize the footprint on the user. A single lead, clinical grade elec-trocardiogram (ECG), along with 3 axes of acceleration are recorded while a userwearing the device carries out his/her daily activities. The monitor itself consists ofa central PCB that contains an electrode and the majority of the electronics, alongwith either one or two additional electrodes that are connected to smaller electrodePCBs. The monitor can be configured such that any given electrode can act as aninput or an output. The system can record ECG and acceleration for over 1 weekand consumes 7.3 mW.

To confirm the quality of the ECG recorded by the device, a clinical test wasperformed. Individuals wore both the device discussed in this thesis and a clinicalECG recorder while engaging in physical activities such as sitting, standing, andrunning. Four participants have been tested at this time. QRS sensitivity and QRSpositive predictability were determined for each ECG trace. The cardiac monitoroutperformed the clinical recorder in all interventions. It should be a viable alternativeto conventional monitors. Additional participants will be tested as part of futurework.

Thesis Supervisor: Dr. Charles G. SodiniTitle: Clarence J. LeBel Professor

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4

Acknowledgments

I would first like to thank Professor Charlie Sodini, my thesis supervisor, for his

support, mentorship and guidance throughout the MEng thesis. I look forward to

working with him over the next few years as I pursue further graduate studies. I

would also like to thank Eric Winokur, who was my UROP supervisor when I first

started working on this project. Eric helped me get up to speed on the project and

learn how to be an effective graduate student. It was his mentorship that helped

me make an effective transition to graduate life and decide to pursue the research

further. Collin Stultz and Thomas Heldt both provided a valuable perspective on

the underlying physiology as it interacts with my work. They both helped me make

sure I had the facts straight. David He, Sabino Pietrangelo, and Bruno Do Valle

helped me when I had questions about anything from system level design to which

microcontroller to use. I would also like to thank all the other members of our office

space, who provided a great environment to work in. Bryan Haslam, Cathy Ricciardi,

and Ankit Gordhandas were vital contributors to the clinical testing at MIT. It could

not have happened without them. I would also like to thank Texas Instruments and

Analog Devices, Inc. for the parts samples I used for the monitor. I would like to

thank all my friends and family for their support and encouragement over the past

school year. Last but certainly not least, I would like to thank my parents, Mark and

Maureen Delano. Although I don’t get to see them or call them as much as I should,

I know that they will support me in whatever I do.

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6

Contents

1 Introduction 15

1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

1.2 Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

1.3 The Electrocardiogram . . . . . . . . . . . . . . . . . . . . . . . . . . 17

1.4 Using the Electrocardiogram . . . . . . . . . . . . . . . . . . . . . . . 22

1.5 Previous Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

2 Design 29

2.1 Electrical Specifications and Challenges . . . . . . . . . . . . . . . . . 29

2.1.1 ECG Signal Requirements . . . . . . . . . . . . . . . . . . . . 29

2.1.2 Accelerometer Signal Considerations . . . . . . . . . . . . . . 36

2.1.3 System Level Requirements . . . . . . . . . . . . . . . . . . . 36

2.2 Software Specifications and Challenges . . . . . . . . . . . . . . . . . 37

2.3 Mechanical Specifications and Challenges . . . . . . . . . . . . . . . . 38

3 Implementation 41

3.1 Final System Overview . . . . . . . . . . . . . . . . . . . . . . . . . . 41

3.1.1 Central Board . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

3.1.2 Electrode boards . . . . . . . . . . . . . . . . . . . . . . . . . 43

3.1.3 Cardiac Monitor Placement . . . . . . . . . . . . . . . . . . . 43

3.2 Hardware . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

3.2.1 Analog Front End . . . . . . . . . . . . . . . . . . . . . . . . . 47

3.2.2 Digital Back End . . . . . . . . . . . . . . . . . . . . . . . . . 49

7

3.2.3 Power Management Circuitry . . . . . . . . . . . . . . . . . . 51

3.3 Software . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

3.3.1 Final Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . 53

3.3.2 Allocate space and structures . . . . . . . . . . . . . . . . . . 53

3.3.3 Initializing the System . . . . . . . . . . . . . . . . . . . . . . 56

3.3.4 Checking the micro SD card . . . . . . . . . . . . . . . . . . . 58

3.3.5 Selecting the available flash memory . . . . . . . . . . . . . . 58

3.3.6 Sampling Timer Interrupt . . . . . . . . . . . . . . . . . . . . 59

3.3.7 Saving Data to Serial Flash . . . . . . . . . . . . . . . . . . . 60

3.3.8 Saving Data to micro SD . . . . . . . . . . . . . . . . . . . . . 61

3.3.9 Importing the data . . . . . . . . . . . . . . . . . . . . . . . . 61

3.4 Cardiac Monitor Specifications . . . . . . . . . . . . . . . . . . . . . . 62

3.4.1 ECG Specifications . . . . . . . . . . . . . . . . . . . . . . . . 62

3.4.2 Accelerometer Specifications . . . . . . . . . . . . . . . . . . . 63

3.4.3 System Specifications . . . . . . . . . . . . . . . . . . . . . . . 64

4 Clinical Test 67

4.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

4.1.1 ECG Signal Quality . . . . . . . . . . . . . . . . . . . . . . . 68

4.1.2 Comfort Level . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

4.1.3 Activity Level . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

4.1.4 Creating a Suite of Physiological Signals . . . . . . . . . . . . 68

4.2 Protocol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

4.3 Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71

4.3.1 Cardiac Monitor Signal Quality . . . . . . . . . . . . . . . . . 71

4.3.2 Cardiac Monitor Comfort Level . . . . . . . . . . . . . . . . . 73

4.4 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

4.4.1 Cardiac Monitor Signal Quality . . . . . . . . . . . . . . . . . 73

4.4.2 Cardiac Monitor Comfort Level . . . . . . . . . . . . . . . . . 74

4.4.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75

8

5 Conclusions 77

5.1 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77

5.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79

5.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80

A Micro SD Code 81

A.1 Micro SD Card Header File . . . . . . . . . . . . . . . . . . . . . . . 81

A.2 Micro SD .C File . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84

9

10

List of Figures

1-1 The ECG waveform . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

1-2 12 Lead ECG . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

1-3 Einthoven’s Triangle . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

1-4 The Frontal Axis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

1-5 Precordial Electrode Placement . . . . . . . . . . . . . . . . . . . . . 21

1-6 Dynamic Time Warping . . . . . . . . . . . . . . . . . . . . . . . . . 23

1-7 A Holter Monitor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

1-8 The Netguard Device . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

1-9 The V Patch . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

1-10 The IMEC Patch . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

1-11 Wearable ECG Patch dimensions . . . . . . . . . . . . . . . . . . . . 27

2-1 Three Electrode Placement . . . . . . . . . . . . . . . . . . . . . . . . 31

2-2 Two Electrode Placement . . . . . . . . . . . . . . . . . . . . . . . . 32

2-3 The Instrumentation Amplifier . . . . . . . . . . . . . . . . . . . . . . 34

2-4 Displacement Currents . . . . . . . . . . . . . . . . . . . . . . . . . . 34

2-5 A Right Leg Drive Circuit . . . . . . . . . . . . . . . . . . . . . . . . 35

2-6 Wearable ECG Patch on subject . . . . . . . . . . . . . . . . . . . . . 39

3-1 Three Electrode Wearable, Long Term Cardiac Monitor . . . . . . . . 42

3-2 The Central Board . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

3-3 The Electrode Board . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

3-4 Electrode Board as Input . . . . . . . . . . . . . . . . . . . . . . . . . 44

3-5 Electrode Board as Output . . . . . . . . . . . . . . . . . . . . . . . . 44

11

3-6 Three Electrode Cardiac Monitor Worn . . . . . . . . . . . . . . . . . 45

3-7 Two Electrode Cardiac Monitor Worn . . . . . . . . . . . . . . . . . 46

3-8 Monitor Worn Under Shirt . . . . . . . . . . . . . . . . . . . . . . . . 46

3-9 Block Diagram of Overall System . . . . . . . . . . . . . . . . . . . . 47

3-10 Analog Front End . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

3-11 Three Electrode Board With Battery . . . . . . . . . . . . . . . . . . 52

3-12 Final Algorithm Flowchart . . . . . . . . . . . . . . . . . . . . . . . . 54

3-13 An Example Flash Block . . . . . . . . . . . . . . . . . . . . . . . . . 60

3-14 Saving to Flash . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

4-1 Participant Ready for Testing . . . . . . . . . . . . . . . . . . . . . . 69

4-2 Sequence of Interventions . . . . . . . . . . . . . . . . . . . . . . . . . 70

4-3 Recording Times . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70

4-4 Participant on treadmill . . . . . . . . . . . . . . . . . . . . . . . . . 71

4-5 ECG While Running . . . . . . . . . . . . . . . . . . . . . . . . . . . 75

4-6 ECG While Standing . . . . . . . . . . . . . . . . . . . . . . . . . . . 76

4-7 ECG While Supine . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76

5-1 First Revision of Electrode Board . . . . . . . . . . . . . . . . . . . . 78

12

List of Tables

1.1 Existing device specifications . . . . . . . . . . . . . . . . . . . . . . . 26

2.1 ECG Signal Quality Requirements . . . . . . . . . . . . . . . . . . . . 30

2.2 Accelerometer Signal Quality Requirements . . . . . . . . . . . . . . 36

2.3 Overall system specifications . . . . . . . . . . . . . . . . . . . . . . . 37

3.1 GPIO configuration . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

3.2 GPIO descriptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

3.3 ECG Signal Quality Requirements and Measurements . . . . . . . . . 62

3.4 ECG Signal Quality Specifications by Design . . . . . . . . . . . . . . 62

3.5 Accelerometer Signal Quality Requirements . . . . . . . . . . . . . . 63

3.6 Overall system specifications . . . . . . . . . . . . . . . . . . . . . . . 64

3.7 Current Dissipation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64

3.8 Write/ Read Times . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

4.1 QRS Sensitivity and Positive Predictivity . . . . . . . . . . . . . . . . 74

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Chapter 1

Introduction

A wearable, long term cardiac monitor has been developed. In this chapter, the

motivation behind wearable monitors will be presented. Specific objectives of this

thesis will be described, along with previous work in the field.

1.1 Motivation

Cardiovascular disease is the leading cause of death in the United States, accounting

for 32.8% of total deaths in the United States in 2008 [1]. The United States spent al-

most $300 billion on the direct and indirect costs of cardiovascular disease and stroke.

Although the rate of death attributable to cardiovascular disease has declined 30.6%

since 1999, the prevalence of traditional risk factors such as hypertension, obesity and

smoking remains an issue. As the United States population ages, enormous pressure

is being placed on the health care delivery system to maintain quality of care while

reducing overall costs. The current quality of care can only be maintained if the

health care delivery system becomes significantly more efficient.

One way to reduce costs associated with health services while maintaining quality

of care is to provide systems that monitor an individual as they go about their daily

activities, reducing the number of doctor’s visits required. Physicians can use these

systems to monitor individuals recovering from an existing cardiac condition, those

at risk, and those experiencing cardiac discomfort. Monitoring an individual at home

15

and over longer periods of time can help a physician track disease progression. Earlier

detection of a disease state can then lead to earlier intervention and treatment. In

addition to monitoring disease progression, physiological monitoring on a day-to-day

basis can help establish normal physiology for an individual and can provide feedback

for more targeted treatments.

Recent studies suggest that risk of death in patients who have suffered heart

attacks can be predicted using the electrocardiogram (ECG) [2] [3]. These studies

analyzed up to 24 hours of continuous ECG data from patients in their hospital beds.

They developed computational methods that analyze the similarity of neighboring

heart beats and used these methods to predict whether a patient would live or die.

These studies are currently limited to data taken from individuals who have already

had a cardiac event and whose ECG is recorded shortly thereafter the event while

they are recovering. Collecting long term ECG data from both patients with existing

cardiovascular conditions and those at risk individuals may help further development

of these risk stratification methods. Additionally, collecting long term ECG data

along with an estimate of activity level (such as from an accelerometer) while an

individual carries out his or her daily activities may give a physician a better estimate

of that individual’s cardiac health than ECG alone.

1.2 Objectives

The goal of this thesis is to develop and validate a wearable, long term cardiac moni-

tor. The system should be able to record ECG and acceleration data continuously for

at least one week. It must be able to withstand every day physical activity and be as

comfortable and unobtrusive as possible. The device must perform on par or better

than the devices that exist today. It could then be used as an alternative to clinically

available monitors, but would have a much smaller form factor and fewer wires. The

monitor can be used to collect data from patients who have suffered a cardiac event

and those at risk as they go about their daily activities. This will allow physicians

to track disease progression and allow researchers to develop methods to predict and

16

prevent serious cardiac events.

The cardiac monitor will be validated in a clinical test conducted at the Clinical

Research Center (CRC) at MIT. Healthy individuals will perform a series of different

interventions while wearing both the monitor developed in this thesis and a commer-

cially available monitor. Interventions will include activities ranging from lying down

to running in order to simulate what wearing the monitor throughout the day would

be like. The cardiac monitor will be validated if it performs as well (if not better)

than the commercially available monitor and is able to withstand every day activity

while being both reasonably comfortable and unobtrusive.

1.3 The Electrocardiogram

Before discussing previous work in wearable heart monitor technology, it is important

to understand the basics of the electrocardiogram (ECG) itself. The ECG has become

a routine part of any complete medical evaluation and has been used as a diagnostic

test since its discovery over 70 years ago [4]. Because electricity is conducted through

the heart muscle (known as the myocardium), many (but not all) types of damage

to the heart tissue can be detected with an ECG. The ECG waveform allows one to

infer information about electrical activity associated with different aspects of a heart

beat and is therefore of particular value for assessing an individual’s cardiac rhythm

and heart health.

A normal cardiac rhythm is referred to as a “sinus” rhythm because of its orig-

ination in the sinoatrial node (S-A node). Disruptions of this normal sinus rhythm

are known as arrhythmias. Each heart beat is triggered by “pacemaker” cells in the

S-A node. These cells generate action potentials at 60 – 100 beats per minute (while

at rest). Action potentials depolarize the tissue as they propagate throughout the

myocardium in a predefined way, causing muscle tissue to contract. After the action

potentials leave the S-A node, they depolarize the two upper chambers of the heart

known as the atria, and then move to the atrioventricular node (A-V node). This

node sits between the atria and the lower two chambers of the heart known as the

17

ventricles. It acts as a backup pacemaker at a lower rate of 40 – 60 beats per minute.

The A-V node also delays the electrical impulses, slowing them down by about 120

ms to give the atria enough time to eject their blood into the ventricles before the

ventricles contract. After the action potentials leave the A-V node, they move to an

area known as the “His” bundle and down the left and right bundle branches. Con-

ductive fibers known as Purkinje fibers depolarize the ventricles, starting from the

left ventricle and swinging to the right. After the ventricles have been depolarized

and contract, the cycle starts over with another impulse from the S-A node.

Figure 1-1: An ECG waveform is composed of action potentials originating in differentareas of the heart. The ECG waveform recorded at the skin is the superposition ofthese different action potentials. Source: [5]

The ECG represents the electrical activity of an ensemble of cells in the my-

ocardium. It is a differential measurement across the surface of the body and can be

thought of as a vector measurement of electrical potential. A typical ECG waveform

(as shown on the right side of Figure 1-1) consists of three primary features: the P

wave, the QRS complex, and the T wave. Each wave corresponds to the electrical

18

activity in specific parts of the heart. The P wave comes first and represents the

depolarization of the atria. The delay between the P wave and the QRS complex is

known as the PR interval. This interval signifies the delay that occurs in the A-V

node that gives the atria time to contract before depolarizing the ventricles. The

QRS complex represents depolarization of the ventricles, and is usually the strongest

wave in an ECG. The last wave is the T wave and it represents the repolarization of

the ventricles. The repolarization of the atria is usually hidden in the QRS complex.

Taking a differential measurement of the electrical potential on the body surface at

different locations generates different ECG vectors. A standard clinical ECG consists

of 12 different vectors known as “leads.” Six of these leads are in the plane parallel to

the body and are known as “frontal” ECG leads. The other six ECG leads are views

of the heart in the plane perpendicular to the body and are known as “pre-cordial”

leads. A view of all 12 ECG leads can be seen in Figure 1-2.

Figure 1-2: A vector view of the standard 12 Lead ECG. The frontal leads are lightblue and the pre-cordial leads are dark blue. Source: [6]

The frontal ECG leads are formed from three different electrodes placed on the

body, with an optional fourth electrode used as a reference. These electrodes are

usually placed on the right arm (RA), left arm (LA), and left leg (LL). The optional

reference electrode is usually placed on the right leg (RL). The three sensing electrodes

(RA, LA, and LL) form what is known as Einthoven’s triangle (see Figure 1-3). The

19

six frontal leads are derived from this triangle. Leads I, II and III are formed directly

from the triangle itself. An additional three leads, known as the augmented limb

leads (augmented foot, augmented right, augmented left) are formed by subtracting

the average of two electrode potentials from the value of the third. These leads are

known as augmented leads because their amplitude is 1.5 times the amplitude of the

frontal leads. Each lead is derived from one of the three sensing electrodes using the

equations provided in Equation Array 1.1. The vector representation of each frontal

lead is shown in Figure 1-4.

Figure 1-3: Einthoven’s triangle, formed by the right arm, left arm and left legelectrodes. These three electrodes form the basis for the frontal axis. Source: [7]

I = LA−RA (1.1)

II = LL−RA (1.2)

III = LL− LA (1.3)

aV F = LL− 1

2(LA+RA) (1.4)

aV R = RA− 1

2(LA+ LL) (1.5)

aV L = LA− 1

2(RA+ LL) (1.6)

The remaining six leads of the 12 lead system are the pre-cordial leads. The

electrodes V1–V6 are placed on the chest as demonstrated by Figure 1-5. The lead is

20

Figure 1-4: The frontal axis of the ECG consists of six vectors derived from threeelectrodes: left arm (L), right arm (R), and left leg (F). Source: [7]

the difference between the potential at the electrode site and the average potential of

RA, LA and LL. This can be thought of as the difference between the center of the

body and the pre-cordial electrode, which creates a vector perpendicular to the body.

Figure 1-5: The electrodes V1–V6 are placed on the chest roughly in a line. Source:[7]

21

1.4 Using the Electrocardiogram

When using the ECG to assess heart health, the 12 lead ECG is the clinical standard.

The combination of 12 different leads gives the physician a view of the heart’s electrical

activity from a variety of different views. Although 12 lead ECG is standard, it is not

always required. Detecting an arrhythmia, for example, only requires one ECG lead,

so long as that lead has a good view of the different ECG waves. When analyzing

an ECG lead for arrhythmias, there are three important steps [4]. The first step is

to find the QRS complexes and examine their rate, regularity and shape. The next

step is to find the P waves, check if each P wave corresponds to a QRS complex,

examine their shape and check for anything else irregular about their pattern. Most

arrhythmias can be identified using this information.

The risk stratification method known as Morphology Variability can also be per-

formed using a single ECG lead [2] [3]. This method uses the ECG and compares

adjacent beats. It is interested in small differences between the two beats that are

often undetectable by the naked eye. These small differences can change over time.

Because two neighboring beats are not identical, dynamic time warping is used to

compare the correct parts of each beat (see Figure 1-6). Morphology Variability was

shown to be higher in those who died after cardiac events than in those who did not

[2]. Additionally, it provides information about the patient that is uncorrelated with

other risk stratification methods [3].

It is useful to be able to record an ECG while an individual is carrying out his/her

daily activities. To record ECG in this ambulatory setting, wearable cardiac monitors

are used. When an individual is having heart problems or discomfort (especially if the

origin of which cannot be determined from a routine checkup), a physician often has

the individual wear a device known as a Holter monitor for 24 – 48 hours [8] (see Figure

1-7). A typical Holter monitor measures one or more ECG leads using electrodes

placed on the chest. The electrodes are connected to wires that are connected to a

central processing unit, usually worn on a belt or in a pocket. Although in wide use

today, there are a number of shortcomings with a standard Holter monitor. First, the

22

Figure 1-6: Dynamic Time Warping as applied in [2] [3]. Vertical lines connectcorresponding samples between the two beats. If samples taken at equally spacedintervals from the beginning, different parts of the beats could be compared. Dynamictime warping forces similar parts of the two waveforms to be compared. Source: [2]

wires that attach to the electrodes can be a significant noise source, especially during

higher levels of physical activity such as walking or running. They are cumbersome

to wear and can be inadvertently detached if pulled. With many Holter monitor

implementations, even if the device is worn continuously, only small subsets of the

data is clean enough for use [3]. Additionally, although some newer Holter monitors

can record data for up to 1 week [9], patients can have arrhythmias that occur once

every ten days to one month that are not recorded by the Holter monitor.

Figure 1-7: A patient wearing a Holter Monitor. Source: [10]

To capture events that occur less frequently, patients can be fitted with devices

known as event monitors, which can be worn for a month or longer [11]. However,

event monitors typically only save ECG data around the irregular cardiac episode,

23

which minimizes the amount of analysis that can be performed. Continuous long-term

data allows the clinician to detect overall heart health trends and possibly see initial

markers before the cardiac irregularity occurs [12]. Longer term ECG recordings can

be used both to develop new risk biomarkers and stratify risk of individual patients

[2] [3].

1.5 Previous Work

Several groups have worked on wearable monitors to improve the form factor of wear-

able monitors and increase patient compliance [13] [14]. In this section, a few note-

worthy examples will be discussed. The first such device is the Netguard, developed

by Mindray (see Figure 1-8). The Netguard is a small device that takes a single ECG

lead using two custom electrodes worn at the chest as demonstrated in Figure 1-8. It

is designed for in hospital use and has a wireless ECG monitor that weighs less than

an ounce and communicates with a standard PC at a nurse’s station. The device

can detect asystole (when the heart stops beating) and ventricular fibrillation (when

the ventricles contract in a rapid and uncontrollable way). When a dangerous car-

diac rhythm is detected, an alert is sounded and an ECG display with the dangerous

rhythm is displayed. The nurse can confirm the alert and call an emergency as per

hospital protocol.

Figure 1-8: The Netguard device developed by mindray. Source: [15]

One of the benefits of the Netguard is that it costs a fraction of that of conventional

monitors. Having such a device on all patients in a ward can help reduce a hospital’s

24

potential exposure to liability from incidents that occur to unmonitored patients that

could otherwise have been prevented. However, a limitation of the work is that

the Netguard only works so long as the individual is in range of its base station.

Additionally, once a patient has been admitted to the hospital, it is likely that a full

12 lead ECG would be taken, thus making the Netguard device redundant.

The V patch from Intelesens is similar to the Netguard, but can be used in an

ambulatory setting. The patient wears a device (shown in Figure 1-9) that connects to

electrodes worn at the chest. ECG is monitored continuously and events detected by

the system are transmitted to a base station. From the base station, data is uploaded

to a web-based interface that can be accessed by the physician. The V patch can

automatically detect a number of the most commonly occurring arrhythmias, but

will also respond to a patient alarm button.

Figure 1-9: The V patch device developed by Intelesens. Source [16]

A major benefit of the V patch device is that it can be worn for a week before

recharging. Additionally, the patient wearing the device can go about their daily life

while wearing the device. The patch is designed to minimize the use of wires and

dramatically reduces the effects of motion artifacts. A downside of this device is that

it requires a somewhat bulky base station worn in the patient’s pocket to connect to

the internet.

IMEC (Belgium) has announced the release of a promising ECG device. This

patch will be worn at the chest and can measure three ECG leads (see Figure 1-10).

25

The patch measures heart rate on board and also has a 3 axis accelerometer. The

system on a chip design and Bluetooth low energy radio enables the device to last up

to one month with a 200 mAH battery.

Figure 1-10: The wireless ECG patch developed by IMEC. Source: [17]

One of the advantages of the IMEC patch is that it uses Bluetooth low energy to

transmit its data. While requiring a base station is not ideal, it’s more likely that

a user would already have an existing Bluetooth enabled device and would not have

to carry an additional one with them. However, the IMEC device is limited in that

it does not transmit raw ECG data. It extracts relevant information from the ECG

waveform (heart rate, along with onset, peak and offset of the P, QRS, and T waves).

While this would allow adequate reconstruction of the basic features of the ECG wave

form, this alone would not allow a physician to view the morphology of the waveform.

Specification Netguard V patch IMEC patchBattery Life ? 7 days 1 month

Leads 1 3 3Data Transmitted Events Events Events, Heart Rate, Features

Detectable Arrhythmias 2 types 10 types ?

Table 1.1: Comparison of specifications of existing devices.

The monitors described above are all limited in similar ways. While they improve

on the Holter monitor form factor by reducing the number of wires, they only transmit

26

information about specific cardiac events, or limited information such as heart rate.

Additionally, they all rely on transmitting data to a base station, which limits their

effectiveness when a cell phone or computer is not nearby, and requires the user to

have an additional device with them at all times. This thesis aims to develop a

device that can save high quality ECG data continuously for up to one week, without

requiring the use of a base station.

A first generation of the cardiac monitor was developed prior to the start of the

device presented in this thesis. The first generation device, known as “the patch,”

was fabricated on a flexible PCB and was designed to be completely free of wires (see

Figure 1-11). Different ECG leads (I, II, III or aVF) can be used by selecting three of

the appropriate electrodes as a +/- input or a ground drive. The patch was validated

in a clinical study at the Clinical Research Center (CRC) at MIT. The performance of

the patch was compared with that of a Criticare 504-US ECG recorder with electrodes

placed adjacent to the active patch electrodes.

Figure 1-11: Board dimensions on the wearable ECG patch developed by EricWinokur of the Sodini Group. Photo credit: David He

Overall, the patch performed as well (if not better) than the Criticare monitor.

However, there were a few areas in which the patch could be improved. Specifically,

27

improvements in mechanical reliability and memory capacity can be made. Because

the patch was designed on a single flexible PCB, the board was constrained to move

as one piece, often resulting in broken solder connections that caused the board to

malfunction. Because of limited memory capacity on the patch (128 Mb), the total

possible test duration was less than one day.

In the next several chapters, implementation of a new wearable, long term cardiac

monitor will be presented. In Chapter 2, design requirements and considerations for

developing such a device will be discussed. Implementation of the final prototype

device is described in Chapter 3. Chapter 4 will describe a clinical test that was

conducted to validate the wearable cardiac monitor, along with some preliminary

results. Finally, Chapter 5 will discuss what has been learned from this thesis, along

with future work that will be carried out after this thesis has been submitted.

28

Chapter 2

Design

In the previous chapter, motivation for a wearable, long term cardiac monitor was

presented. This chapter will discuss the design considerations for implementing such a

system. It will outline considerations in three different categories: electrical, software,

and mechanical. Relevant design decisions and background will be discussed.

2.1 Electrical Specifications and Challenges

Electrical considerations for the cardiac monitor are driven by its use model. It must

perform at least as well as commercially available devices, with a small and comfort-

able form factor. It must be able to record ECG and acceleration data continuously

for at least one week.

2.1.1 ECG Signal Requirements

A summary of the electrical specifications relating to ECG signal quality are presented

in Table 2.1. The minimum requirements for the system, along with the desired target

specifications are listed. In the paragraphs below, each specification will be discussed

in detail.

29

Specification Minimum TargetLeads 1 1

Electrodes 2–3 2–3Bandwidth 0.5 – 40+ Hz 0.5 – 100 Hz

Input Referred Noise < 30 µV < 20 µVGain 100–1000+ 100–1700+

ADC Resolution 8+ bits 12 bitsCMRR (@ 60 Hz) 40+ dB 90+ dB

Table 2.1: ECG Signal Quality Requirements

Leads

The cardiac monitor needs to be as unobtrusive as possible. It should have a small

form factor with as few electrodes as possible while maintaining signal integrity. The

device will be used for general monitoring and basic arrhythmia analysis. Individuals

with existing heart conditions can wear the device to give their physician a better

idea of their baseline physiology. Those suspected of having an arrhythmia or other

problem can wear the monitor for longer periods of time (eg. 1 day to 1 week) to help

their physician diagnose a condition that occurs infrequently. For this use model, a

single lead with a good view of the cardiac axis will suffice. Leads I and II both satisfy

this requirement and were selected as the two desired leads for the cardiac monitor.

Electrode Number and Placement

Although only 2 electrodes are required to take a single ECG lead, a third reference

electrode is often used to set the body to a common potential. A 2 electrode imple-

mentation has the advantage that it minimizes the footprint on the user. However,

a 3 electrode implementation has the advantage that it is more robust to noise and

has more options for lead selection. Both possibilities are explored in this thesis.

To obtain a Lead I or Lead II, there are a few different options for electrode place-

ment. In the three electrode configuration, any two electrodes can form a vector with

the third electrode as the reference, so up to three unique vectors can be selected

from the three electrodes. The three electrode monitor, if worn in the configuration

shown in 2-1a, for example, would allow a Lead I, Lead II or Lead III to be selected.

30

However, this configuration might not be comfortable for the user, as wires or elec-

tronics might have to cross over the pectoral muscles and breast tissue. The alternate

configuration in 2-1b provides configuration that should be more comfortable for the

user, but with a good view of Lead II only.

(a) Option One (b) Option Two

Figure 2-1: Two different options for electrode placement in the three electrode con-figuration.

In the two electrode configuration, the electrodes must be placed in the orientation

desired for the lead and only one unique lead is possible. If the electrodes are placed

on the body to obtain a Lead II vector, they would look like that shown in Figure 2-

2a. However, similar to what happened in the three electrode case, this might result

in wires or electronics across the pectoral muscle and breast tissue. An alternate

possibility is that shown in Figure 2-2b. This provides a good view of Lead I only.

For both the three and two electrode implementations, two possibilities for elec-

trode placement were presented. In the three electrode case, the most ideal configu-

ration would provide the best view of Lead II, whereas in the two electrode case, the

most ideal configuration would provide the best view of Lead I.

ECG Bandwidth

ECG signal bandwidth requirements vary depending on the application. For non-

diagnostic ECG, a bandwidth of 0.5 to 40 Hz is typical. For diagnostic quality ECG,

31

(a) Option One (b) Option Two

Figure 2-2: Two different options for electrode placement in the two electrode con-figuration.

the bandwidth must be at least 0.05 to 150 Hz. A lower high-pass frequency is

required in diagnostic quality ECG to allow accurate ST segments to be recorded.

The ST segment is not as relevant for arrhythmia analysis, so a non-diagnostic ECG

bandwidth can be used. The higher high-pass frequency in non-diagnostic ECG helps

reduce baseline drift and is preferred for use with monitoring devices. The high-pass

frequency of the monitor will be set to 0.5 Hz, and the low-pass frequency will be set

to 125 Hz.

Noise and Gain

In a typical ECG, the P wave is the smallest feature of interest. A typical P wave

has an amplitude of 200 – 300 µV. The input referred noise should be much lower

than 200 µVrms for detection of the P wave. It is typically specified to be less than

30 µVrms. A typical QRS complex is the largest feature of interest and can have

an amplitude of 2 mV or greater. This value sets the upper bound on the overall

system gain. The amplitudes of these waves varies person to person. A system with

variable gain is needed to account for potential differences between the amplitude of

different individuals’ biosignals. Gains ranging from 100 to 1000 will provide adequate

amplification for signals as large as tens of millivolts and as small as hundreds of

microvolts.

32

ADC Resolution

The bandwidth, noise and gain specifications have now been set. The next consid-

eration is the ADC resolution. As an example, consider a single supply system at

2.5 V with an 8 bit ADC. An ECG with a QRS complex of 2 mV, and a P-wave of

200 µV is the input to the system. A gain of 400 would result in a QRS complex of

800 mV and a P-wave of 80 mV. This results in about 3 bits of resolution for the

P-wave. However, from experience with a previous iteration of the cardiac monitor,

an ADC resolution of 8 bits resulted in a small but noticeable amount of quantization

error. Greater than 8 bits of resolution (with sufficient gain) will meet the signal

requirements. The target ADC resolution is set to 12 bits.

CMRR

The ECG is a differential measurement between two electrodes. Because the signal

amplitude is on the order of millivolts or less, an amplifier with high differential gain

is required. The most common topology used for ECG and other biopotentials is the

Instrumentation Amplifier (IA). The IA is a differential operational amplifier with

input buffers connected in a resistor totem pole (see Figure 2-3). The differential

gain of the circuit is avd = 1 +(

2R1

Rgain

)R3

R2. Connecting Rgain in the method shown

increases the differential gain of the first stage of the circuit while maintaining a

common mode gain close to one. This gives the circuit a high CMRR. CMRRs of

greater than 90 dB are common in IC implementations of the IA.

Reducing Interference in ECG

Although an IA has a high CMRR, large potential differences between the body

and the system common can result in common mode voltages outside the IA’s input

range. Additionally, 60 Hz interference from electronic devices can be converted into

a differential signal that cannot be eliminated even with an infinitely high CMRR.

60 Hz interference is most often caused by an impedance mismatch between the two

sensing electrodes [19]. If powerline interference capacitively couples onto electrode

33

Figure 2-3: A block diagram view of an instrumentation amplifier. Source: [18]

Figure 2-4: Displacement currents when measuring ECG can cause a differentialvoltage difference at the IA if Z1I1 6= Z2I2. Either an impedance mismatch or adisplacement current mismatch can cause this differential voltage.

leads, displacement currents are induced. A mismatch in electrode impedance can

result in differential voltages at the amplifier inputs (see Figure 2-4). Common mode

voltages can also be converted to differential voltages by the “potential divider effect”

[20].

There are three common ways to reduce the effect of large common mode voltages

and 60 Hz interference. The first method uses a third electrode, while the second

method uses capacitive coupling and filtering. The third method can be used in

conjunction with either the first or the second method and involves actively buffering

the biosignal at the electrode site.

The first method to reduce common mode voltages and 60 Hz interference involves

a circuit known as a driven right leg (DRL) circuit [21]. This circuit takes a standard

34

two electrode lead and ECG amplifier (usually an IA) and adds a third, driven elec-

trode (see Figure 2-5). The additional circuitry measures the common mode voltage

of the two electrodes and negatively amplifies the resulting signal. The amplifier is

referenced to the circuit common and so the body is driven to that potential. Any

60 Hz interference present is also negatively amplified and driven back into the body,

reducing its amplitude. This approach works well to drive the body within the circuit

voltage rails and eliminate 60 Hz interference, but requires a third electrode.

Figure 2-5: An example of a right leg driven circuit. [22]

The second method to reduce large common mode voltages is to capacitively

couple the biosignal into the circuit. A resistor connected to the circuit common

combined with the DC blocking capacitor form a high pass filter at the electrode

site and reference the resulting signal to the circuit common. This approach does

not require an additional electrode, but also does not remove any 60 Hz interference.

Additional filtering is usually required. The 60 Hz interference can be eliminated by

a notch filter, implemented in analog or digitally anc can be done before sampling

the signal or in post-processing.

The third method to reduce common mode voltages specifically reduces 60 Hz

interference. Because most 60 Hz interference is caused by an impedance mismatch

between the electrodes, a strategy that reduces this impedance can reduce inter-

ference. It has been shown that actively buffering a biopotential can reduce signal

interference by up to 40 dB [19]. This is because a buffer has a low output impedance.

35

When placed right at the electrode site, the biopotential becomes a low impedance

signal. With a lower impedance for each electrode, the difference between the two

electrode impedances is also reduced. Actively buffering the electrode site can be

used in combination with both the first and second methods described above.

2.1.2 Accelerometer Signal Considerations

Signal requirements for the accelerometer are not as constrained as that of the ECG.

The most important considerations are the acceleration range, resolution, and sample

rate. To determine a reasonable acceleration range, a prototype board with an ac-

celerometer was worn while an individual tried to generate large accelerations (such

as by jumping up and down and running). Acceleration values were usually within

± 4g, so that should be sufficient for obtaining the full range of accelerations. How-

ever, in practice, the accelerometer on the cardiac monitor (ADXL346) has a range

vs resolution scheme such that a ± 8g range can be obtained with the same LSB

value as with ± 4g range. At ± 8g, the ADXL346 has a full resolution of 12 bits. In

a previous iteration of the cardiac monitor, acceleration was recorded at both 2 Hz

and 250 Hz. While 250 Hz was clearly oversampled, 2 Hz may have been too low. As

a compromise, a sample rate of 12.5 Hz was selected.

Specification Minimum TargetRange ± 4g ± 8g

Resolution 8 bits 12 bitsSample rate 2 Hz 12.5 Hz

Table 2.2: Accelerometer Signal Quality Requirements

2.1.3 System Level Requirements

A summary of the desired system specifications are listed in Table 2.3. Both minimum

and desired specifications are listed. Further details of each specification are provided

below.

The signal requirements and use model for the cardiac monitor provide system

36

Specification Minimum TargetTest duration 24 hours 1+ weeks

Memory 128 MB 1+ GBPower dissipation < 9.7 mW < 9.7 mW

Table 2.3: Overall system specifications

level electrical requirements. To meet the bandwidth requirement, the ECG is sam-

pled at 250 Hz. The accelerometer is sampled at 12.5 Hz. Allocating 2 bytes per

sample, (250 + 3 ∗ 12.5) ∗ 2 = 575 bytes of data are generated each second, and about

2 MB in an hour. To record for a full week, over 300 MB of space is required (not

including overhead). The data can either be saved on board or transmitted to a base

station and/or cell phone. Because the device needs to be able to sample continu-

ously and last at least one week, while maintaining a small footprint on the user, data

was saved on board. Transmitting the data to a base station / cell phone is power

intensive to do continuously and also requires the user to wear an additional device

or be located near a base station at all times.

Because all data will be stored on board, high density memory must be used. A

micro SD card, commonly used in devices such as cameras, is well suited to this task.

However, writing to a micro SD card requires high write currents and takes on the

order of several hundred milliseconds. Most low power microcontrollers have low on

board memory, so the system must have adequate space on the microcontroller or use

an additional memory source for buffering the data. For a test duration of at least

one week, a battery with several hundred milliamp hours is required. A 600 mAH

battery, for example, could support an average current of 9.7 mW for up to one week

at a supply voltage of 2.7 V.

2.2 Software Specifications and Challenges

The software requirements for the cardiac monitor are straightforward. The software

must be able to sample the ECG and accelerometer waveforms continuously at 250 Hz

and 12.5 Hz, respectively. Data must be sampled and saved continuously. Addition-

37

ally, the software should be able to control the system to keep the power consumption

as low as possible. A low power microcontroller is best suited to this task. The mi-

crocontroller must have enough communication ports for all the peripheral devices

(the accelerometer and memory) and enough I/O ports for electrode configurability,

gain configurability, chip selects, low power operation and debugging.

2.3 Mechanical Specifications and Challenges

The mechanical requirements for the cardiac monitor are not easily quantifiable. The

most important mechanical requirement is that the device be robust, yet comfortable.

The board needs to last a week under ambulatory conditions, and be as unobtrusive

as possible. The mechanical requirements for the device must be achieved while

maintaining the signal quality requirements discussed in Section 2.1.1.

Work on the first generation device first mentioned in Section 1.5 helped provide

feedback on a form factor that might achieve these goals. The first generation device

was fabricated on a flexible “L” shaped PCB and was designed to be completely free of

wires. The components of the board were distributed on the top surface of the PCB.

Although the device performed properly electrically, it was not as robust as the use

model requires. Because the patch was all on a single flexible PCB, it was constrained

to move as one piece. When worn, the device would bend and solder connections

would break. If the board had already been coated in Paralene-C for water and

sweat proofing, this rendered the affected board useless. Additionally, because the

board was wide around the electrode sites, it did not always remain flush against

the electrodes when worn (see Figure 2-6). This caused loose electrode connections,

especially during heavy activity such as walking briskly or running. Finally, the board

was not flexible or comfortable enough for use with women. The board is worn on

the sternum and is too wide and not flexible enough with breast tissue present.

These issues suggest that a single flexible PCB with circuit components distributed

on the surface is not an ideal form factor. A PCB that is more rigid with circuitry

concentrated in a smaller area might achieve better results. If this is done, connections

38

Figure 2-6: A view of the top of the ECG patch while worn.

from this central board to the electrodes must be made, either with flexible PCB,

wires, or another interconnect. Additionally, because the biopotential will be buffered

at the electrode site, circuitry is needed close to the electrode. One solution is to create

an additional PCB that interfaces with only the electrodes at the electrode site. The

PCB would be very small and sit on top of the electrode itself. These small PCBs

would connect to the larger, more central PCB with an interconnect.

39

40

Chapter 3

Implementation

This chapter will describe the final implementation of the cardiac monitor. First, an

overview of the cardiac monitor’s form factor and how it is worn on the body will

be described. Next, diagrams and explanations of each aspect of the system will be

provided. Finally, measurements of the performance of the system versus the desired

specifications discussed in Chapter 2 will be presented. Validation of the cardiac

monitor in a clinical setting can be found in Chapter 4.

3.1 Final System Overview

The final implementation of the cardiac monitor consists of a central board, along with

either one or two electrode attachments (see Figure 3-1). The additional electrodes

attach to the central board via wires and solder pads on each board. Each electrode

connects to a conventional 3M2560 red dot wet electrode. In the three electrode

implementation, the system is designed such that any electrode can act as an input

or output. Details about electrode configuration and setup are provided in section

3.2.2. In the two electrode implementation, the electrode configuration circuitry is

eliminated to reduce the footprint on the user. Without a third electrode, the two

electrode implementation requires capacitive coupling at the electrode inputs. The

input circuitry for both implementations is discussed in Section 3.1.2.

41

Figure 3-1: The wearable, long term cardiac monitor (three electrode implementa-tion).

3.1.1 Central Board

Solder joints on a previous, more distributed implementation of the cardiac monitor

occasionally broke when the PCB was flexed. Therefore, for this iteration of the

cardiac monitor, the majority of circuitry is concentrated on the central board. It

is 5.5cm wide by 4.2cm tall in the three electrode configuration and 5cm wide by

3.6cm tall in the two electrode configuration, only slightly larger than the 3M2560

electrodes (4.1cm by 3.5cm). The boards are 4 layers and 0.066cm thick. They has

been fabricated with Dupont FR material to allow them to bend slightly when worn.

All circuitry (other than that which must be at the additional electrode sites) is

located on these boards. A close up view of the three electrode central board can be

seen in Figure 3-2.

42

(a) Top (b) Bottom

Figure 3-2: The Central Board

3.1.2 Electrode boards

In most ECG monitors, only an electrode exists at the electrode site. This electrode is

then connected to the main system with long wires. However, in this cardiac monitor,

the biopotential at the electrode site is actively buffered. As discussed in section 2.1.1,

it has been shown that actively buffering the electrode signal can reduce power line

interference by up to 40 dB [19]. This requires an op-amp as close to the electrode

site as possible. Additionally, to accommodate both the two and three electrode

implementations, either capacitive or resistive coupling of the ECG input can be

used. Recall that the two electrode implementation requires capacitive coupling as

it does not have a third electrode. Additionally, each electrode can act as an output

(i.e. driven electrode) if used in the three electrode implementation. This electrode

would then act as the driven right leg electrode in the circuit discussed in section

2.1.1. The electrode board is 2cm wide and 2.4cm tall. A close up of the electrode

board itself can be seen in Figure 3-3. The electrode board is configured as an input

in Figure 3-4 and as an output in Figure 3-5.

3.1.3 Cardiac Monitor Placement

The cardiac monitor is worn in one of two configurations, depending on the number

of electrodes in use. In the three electrode case, the central board is placed just

below the sternum. The first electrode board is placed above the central board on

43

Figure 3-3: The Electrode Board

Figure 3-4: The electrode board is configured as an input. The signal from theelectrode is buffered by an op amp that is connected to the IA.

Figure 3-5: The electrode board is configured as an output. The signal from thedriven right leg circuit is connected to the electrode. This electrode then drives thebody.

44

the sternum, and the third electrode is placed just under the left pectoral near where

a V6 electrode would be placed (see Figure 3-6). As discussed in section 2.1.1, one of

three different ECG leads can be selected without moving the electrodes. In the two

electrode configuration, only one lead can be used at a time. Although the device

can be placed anywhere on the chest to obtain an ECG lead, it is placed in a lead

I configuration (see Figure 3-7) with one electrode on the upper sternum and the

other at least 10 cm away parallel to the first electrode. It was shown in [23] that the

maximum ECG signal amplitude was obtained at an interelectrode distance of 10 cm.

The cardiac monitor does not protrude significantly from the chest. As demonstrated

in Figure 3-8, it is very discrete when worn.

Figure 3-6: The three electrode implementation of the cardiac monitor worn at thechest.

3.2 Hardware

The final system implementation consists of three main subsystems: the analog front

end, digital back end, and power management circuitry. A block diagram of the final

45

Figure 3-7: The two electrode implementation of the cardiac monitor worn at thechest.

(a) Cardiac monitor with shirt (Front) (b) Cardiac monitor with shirt (Side)

Figure 3-8: A user wearing the three electrode implementation of the cardiac monitor.The monitor is very discrete and does not protrude significantly from the chest.

46

system can be found in Figure 3-9.

Figure 3-9: A block diagram of the overall system. A simplified version of the AnalogFront End is shown in orange. The Digital Back End consists of the red tinted blocks,and the inputs are shown as red (+), green (-), and black (gnd). Power Managementand the battery are shown in blue.

3.2.1 Analog Front End

The analog front end (AFE) is responsible for acquiring the ECG signal from the

electrodes and amplifying the signal. It also filters the signal before it is sampled

by the ADC. The AFE consists of the electrodes themselves along with any analog

circuitry used in the signal chain before the ADC. A circuit diagram of the analog

front end can be found in Figure 3-10. While the electrode configurability circuitry

influences the analog front end, it is included as part of the digital back end and is

presented in section 3.2.2. The output from each of the sensing electrode goes through

two different paths. The first path is used to amplify the ECG signal and filter it

before it is sampled by the ADC (i.e. ECG signal conditioning). The second path

will be used to generate the common mode feedback signal used to drive the body to

a fixed potential.

47

Figure 3-10: The Analog Front End, beginning with the Instrumentation Amplifier.The signal then goes through a gain selection stage and filter before being sampledby the MSP430.

ECG Signal Conditioning

The AFE’s forward path consists of an instrumentation amplifier and a variable gain

stage with anti-aliasing and smoothing filters (see Figure 3-10). The signal from the

two sensing electrodes provides the input to the instrumentation amplifier, which is

an INA333 configured with a gain of about 20. The output of the INA333 is used as

an input to an OPA333 with input resistance of 300kΩ and a feedback capacitance of

1µF. The output of this amplifier goes to the reference pin of the INA333, effectively

acting as a high pass filter with a cutoff frequency of 0.5 Hz. This high pass filter AC

couples the signal without placing large capacitors in the signal path.

The output of the IA is passed through a SN74CBTLV3125 quadruple FET bus

switch that is connected to four binary weighted resistors. The four resistors act

as the input resistor of an inverting amplifier that follows the IA. With a constant

feedback resistance and 4 bits of selectable input resistance, gains ranging from about

120 to about 1800 can be achieved with a resolution of 120. Gain can be adjusted

using the MSP430 to maximize dynamic range and account for variation in biosignal

amplitude from user to user. The inverting amplifier also acts as a low pass filter.

48

It has a feedback resistance of 1MΩ and a feedback capacitance of 1.2 nF, which

corresponds to a low pass cutoff frequency of approximately 125 Hz. Along with

noise bandwidth reduction, this amplifier serves as an antialiasing filter for the system,

which is sampled at 250 Hz. The output of this amplifier then goes through a single-

pole low pass filter with a cutoff of 285 Hz and then is sampled by the ADC. This

low-pass filter is used to reduce high frequency ADC sample clock feed-through.

Driven Right Leg Circuit

The AFE’s feedback path is the driven right leg circuit. This circuit takes the signal

from the two sensing electrodes and sums them. The sum is then buffered by an

OPA333. The buffered output is then negatively amplified by another OPA333 by

a factor of 39.5 with respect to the circuit midrail. A 120 pF capacitor is included

on the second OPA333. This capacitor in combination with the feedback resistance

creates a low pass frequency of the driven right leg circuit of 3.4 kHz. This ensures

loop stability of the entire front end. Circuit stability in the driven right leg circuit is

discussed in depth in [21]. The driven right leg circuitry is included in the schematic

in Figure 3-10.

3.2.2 Digital Back End

The digital back end is controlled by an MSP430F247 microcontroller. This MSP430

was selected for its low active and standby power, and because it had enough se-

rial peripheral interface (SPI) and I/O ports required for the system. The MSP430

interfaces with all peripheral chips. This includes all the electrode configuration cir-

cuitry), memory, accelerometer, and 3 LEDs for debugging. The MSP430’s internal

12 bit ADC is also used. In this section, the interface between the MSP430 and all

peripheral devices will be described. Software implemented on the MSP430 to con-

trol each peripheral and implement the final algorithm for the cardiac monitor will

be presented in section 3.3.

49

Accelerometer

The accelerometer (ADXL346), like the memory, communicates with the MSP430

via the SPI protocol. It has its own dedicated SPI port. The ADXL346 has multiple

resolution modes that maintain 4 mg resolution. Based on the requirements outlined

in section 2.1.2, the range of the accelerometer was set to ± 8g with full resolution

(12 bits). It samples at 400 samples / second in a “first in first out” (FIFO) stream

mode. The accelerometer has FIFO buffers for each axis that store samples. The

FIFO stream mode samples continuously and overwrites the FIFO buffers with the

most recent samples. Each FIFO buffer can store up to 32 samples. Sampling at

400 samples / sec and saving up to 32 samples corresponds to the first sample in the

buffer being refreshed 400 / 32 = 12.5 times per second, which is the desired sampling

frequency.

Electrode Configurability

In the three electrode implementation, each electrode can be configured as either

a positive input, negative input or output/driven electrode. When an electrode is

configured as an input to the system, the signal at the electrode site is immediately

buffered by an OPA333 low-offset op-amp. The output of each buffer is connected to

two TS5A3359 SP3T switches. The two control lines on each switch are controlled by

the MSP430 and are used to connect one of the three electrodes to either the positive

or negative terminal of the INA333 instrumentation amplifier. Each electrode is also

connected to a third TS5A3359 switch, also controlled by the MSP430. This switch

is connected before the signal is buffered and is used to connect an electrode to the

output of the drive right leg circuit. When an electrode is configured as an output,

the MSP430 uses a TS5A3160 switch to turn off the OPA333 to save power.

Memory

The cardiac monitor has two different types of memory: serial flash memory (2

S25FL128P) and a micro SD card. Because a micro SD card is power intensive

50

and takes hundreds of milliseconds to write to, the serial flash memory is used as a

buffer for the ECG and acceleration data as it is sampled. Once enough data has been

saved to the serial flash memory, the data is written to the micro SD card and can

be accessed by a computer. Two serial flash memories are used for usability reasons.

Bits in the serial flash cannot be changed from 0 to 1 without an erase operation,

which requires that a page be erased before it can be written to again. A bulk erase

of the serial flash memory takes on the order of 120 seconds, which is an inconvenient

duration for the user to have to wait to use the device. By having two serial flash

memories, one device can be used at a time so the user does not have to wait for the

serial flash to erase.

Both the serial flash chips and micro SD card interface with the MSP430 using

SPI. The serial flash chips share an SPI port. Only one chip can be accessed at a time

using the appropriate chip select. The micro SD card has its own dedicated SPI port.

Each serial flash chip has 128 Mbits of memory for a total capacity of 256 Mbits. The

serial flash chips are organized in 256 byte pages that are accessed using three page

address bytes. The lowest page address byte (page address 0) refers to a byte within

the page, and page address 1 and page address 2 act as a 16 bit number used to select

the appropriate page. A micro SD card has a capacity anywhere from 1 MB to 32

GB. In this thesis, testing was done primarily using a Kingston 4 GB micro SDHC

card and a SanDisk 2 GB micro SD card. The micro SD card is broken down into

blocks of 512 bytes. One block of micro SD can hold two pages of flash memory.

3.2.3 Power Management Circuitry

A Cameron Sino CS-EC003SL lithium ion battery is used to power the system. It has

a capacity of 600 mAH at 3.7 V and is 4cm by 3.2cm. The battery is placed on top

of the central board and can be secured with medical tape during testing (see Figure

3-11). Charging for the battery is provided on an external board using an ADP2291.

There are two voltage regulators on the central board. A TPS78227 2.7 V linear

regulator is used to provide power for all analog circuitry. This includes all chips used

in the analog front end, along with the AVCC of the MSP430. A TPS62200 switching

51

Figure 3-11: The three electrode board with battery on top.

regular is used as the digital voltage supply. A switching regulator was used to boost

efficiency during high loads, such as writing to memory.

An undervoltage circuit is used to prevent the battery from discharging below

about 3.1 V. A comparator (TLV3401) connected as a high side voltage sense circuit is

used to provide this undervoltage protection. The negative terminal of the comparator

is connected to a REF3312 1.25 V reference. The battery voltage goes through a

voltage divider and the result is compared to the 1.25 V reference. The output of the

comparator controls a TS5A3166 SPST switch. If the output of the comparator is

high, the battery voltage is high enough and the SPST switch connects the battery

voltage to the voltage regulators. If the output of the comparator is low, the switch

52

is off and the system receives no power.

3.3 Software

The software for the system is implemented on the MSP430 in C. It initializes the

system, samples the ECG and accelerometer, and saves the data to memory. In this

section, the final algorithm will be presented. Details about each particular aspect

of the software will be described, with small code snippets if relevant. Much of the

software implementation was straightforward. However, the micro SD code was the

most difficult to write, despite the open source code available. Code used to initialize

and write to the micro SD card is included in Appendix A.

3.3.1 Final Algorithm

The final algorithm is presented in flowchart form in Figure 3-12. The system first

starts up and confirms that a micro SD card is present before proceeding. It selects

a flash memory and then activates a timer interrupt that overflows once every 4 ms.

When the interrupt is active, the ECG is sampled, and the Accel is sampled every

20 interrupts. After each interrupt, the system checks to see if it should write data

to the serial flash or micro SD card. If needed, writes to these different systems are

executed. Note that the system continues to sample the ECG and the Accelerometer

even while writing to memory. Samples taken during this period are stored in a

separate buffer that is transferred back to the signal buffer at the end of each write.

The different blocks will now be described in more detail.

3.3.2 Allocate space and structures

The first thing the MSP430 does is allocate space for all the buffers used for sampling

and storage. All space is pre-allocated at start up. Each data sample is 12 bytes,

but is treated as a 16 bit (2 byte) sample with the upper nibble of the high byte zero

padded. Each sample is saved as a SAMPLE structure (see Listing 3.1). While not as

53

Figure 3-12: The Final Algorithm run on the cardiac monitor presented in flow chartform. ACount is a counter that increases each time an ECG sample is taken and thenis reset after an accelerometer sample is taken. PCount is a counter that increaseseach time a page is written to flash and then is reset after a micro SD block is written.

54

Listing 3.1: The SAMPLE structure

typedef struct

char BYTE0; // Low by t echar BYTE1; // High by t e

SAMPLE;

Listing 3.2: The STORE structure

typedef struct STORE

char index ; // DATA bu f f e r indexchar tempIndex ; // TEMP bu f f e r indexchar DATA[ 2 5 0 ] ; // DATA bu f f e rchar TEMP[ 2 0 0 ] ; // Temporary ove r f l ow b u f f e r

STORE;

space efficient as possible, it is more simple when analyzing the data. Additionally,

the upper nibble can be used in the future to encode additional information (see

Chapter 5). All samples are saved in STORE structures (see Listing 3.2). These

structures have two buffers with indices. The DATA buffer is the primary data buffer

that is used until it is full and is 250 bytes. The TEMP buffer is 200 bytes. This size

was selected based on write times to memory and should be large enough to prevent

data loss. A large buffer called SPACE is pre-allocated for use as a buffer for the

micro SD transfer.

A structure to keep track of access to the flash memory is also used. Because the

flash memory will be accessed in two different ways, two structures are initiated. The

flash will be written to when a signal buffer is full, and it will be read from when

preparing to write to the micro SD. The FLASH structure keeps track of the flash in

use and the current page address. It also knows how many flash devices are available

in case it reaches the end of a flash device. The FLASH structure is shown in Listing

3.3.

55

Listing 3.3: The FLASH structure

typedef struct

char DeviceNum ; // Current dev i c e numberchar DeviceStart ; // F i r s t d ev i c e numberchar DeviceEnd ; // Last dev i c e numberchar PA2; // Page Address 2char PA1; // Page Address 1

FLASH;

3.3.3 Initializing the System

The first thing the MSP430 does after power-on is initialize the clock setup. The

master clock (MCLK) is generated from an internal oscillator and set to 1 MHz. The

sub-main clock (SMCLK) is used as the clock for the memory and accelerometer and

is also set to 1 MHz. After the clocks have been set up, the I/O pins are configured. A

full listing of the pins used on each port is provided in table 3.1. Detailed descriptions

of each pin used are summarized in table 3.2. The pins corresponding to the three

SPI ports in use are configured, along with all logic circuitry and chip selects. Chip

selects for all peripherals start out high. By default, the system is set for a gain of

about 250. In the three electrode implementation the electrodes are configured to

give a Lead II projection. The I/O mapping in the two electrode configuration is

similar to that of the three electrode, but is not shown for simplicity. A few I/Os

changed position to optimize layout.

Port BIT7 BIT6 BIT5 BIT4 BIT3 BIT2 BIT1 BIT0P1 INS11 INS22 INS21 BUF3 GREEN YELLOW RED NCP2 NC SEL4 SEL3 SEL2 SEL1 BUF2 NC INS12P3 SO2 SI2 CS1 BUF1 SCLK1 SO1 SI1 CS6P4 CS5 GS1 GS2 NC NC NC NC CS2P5 NC NC NC NC SCLK3 SO3 SI3 SCLK2P6 ADC0 NC NC NC NC NC NC NC

Table 3.1: The GPIO configuration of the cardiac monitor.

After the I/Os are configured, the SPI ports for all the peripheral devices are set

up (configuring the I/Os only puts the pins in SPI mode). The timer and ADC are

56

I/O Name BIT DescriptionADC0 P6.7 Output of the AFE / Input to the internal ADCBUF1 P3.4 Set electrode 1 VDD of buffer highBUF2 P2.2 Set electrode 2 VDD of buffer highBUF3 P1.4 Set electrode 3 VDD of buffer highCS1 P3.5 Serial Flash 1 chip selectCS2 P4.0 Serial Flash 2 chip selectCS5 P4.7 Micro SD chip selectCS6 P3.0 Accelerometer chip select

INS11 P1.7 Control logic to select electrode input to IA+ (1)INS12 P2.0 Control logic to select electrode input to IA+ (2)INS21 P1.5 Control logic to select electrode input to IA- (1)INS22 P1.6 Control logic to select electrode input to IA- (2)GS1 P4.6 Control logic to select electrode output to DRL (1)GS2 P4.5 Control logic to select electrode output to DRL (2)

GREEN P1.3 Green LEDYELLOW P1.2 Yellow LED

RED P1.1 Red LEDSEL1 P2.3 Switch connected to 1x resistor in AFESEL2 P2.4 Switch connected to 2x resistor in AFESEL3 P2.5 Switch connected to 4x resistor in AFESEL4 P2.6 Switch connected to 8x resistor in AFE

SI1 P3.1 Slave data in for accelerometerSCLK1 P3.3 Slave clock for accelerometer

SO1 P3.2 Slave data out for accelerometerSI2 P3.6 Slave data in for serial flash

SCLK2 P5.0 Slave clock for serial flashSO2 P3.7 Slave data out for serial flashSI3 P5.1 Slave data in for micro SD

SCLK3 P5.3 Slave clock for micro SDSO3 P5.2 Slave data out for micro SD

Table 3.2: GPIO descriptions

57

also configured. The timer is set to use the SMCLK, divide by 8, and then count up

to 500 (1 MHz / 8 = 125 kHz, 125 kHz / 500 = 250 Hz). The ADC is configured to

sample on each timer interrupt.

3.3.4 Checking the micro SD card

A standard micro SD card is used to transfer data from the serial flash memory to a

form readable by the user. When the system starts, the MSP430 tries to initialize the

micro SD card. If no micro SD card is present, the main loop exits and a red LED

indicates no card is present and that the test has failed. Micro SD card initialization

is described extensively elsewhere [24]. However, open source code available was not

as robust as was needed for this application, and did not always have proper error

checking. The code used for this system is included in Appendix A. Briefly, the

initialization process first powers on the device and waits a few milliseconds before

sending 100 clock pulses with the card deselected (CS high). Next, a reset command

is sent to the card. If this operation succeeds, another command to identify the type

of card is sent. Some micro SD cards use block addressing, and this setting needs to

be appropriately determined to properly address the card. The initialization process

is relatively straightforward, but care must be taken to ensure each operation has

time to complete before starting the next one.

3.3.5 Selecting the available flash memory

Once the system has verified that a micro SD card is present, it checks to see which

(if any) of the two flash memories have been written to previously. This is important

because bits in the serial flash memory can only be changed from 1 to 0. Changing

a bit from 0 to 1 requires an erase operation. Unfortunately, erasing the serial flash

memory can take up to 128 seconds, which is a long delay for the user two wait

before use. To avoid this long wait, the system checks to see if the first flash has been

written to by checking if any of the bits on the first 8 pages are 0. If the flash has

been written to, the MSP430 sends the bulk erase command to the device and tries

58

the second device. If this device is also in use, it sends the bulk erase command again

and waits for the first device to finish. If the second device is not in use, it is used in

place of the first device. Even if the first device is not in use, the system still checks

the second device and issues the bulk erase command for future use.

3.3.6 Sampling Timer Interrupt

Timer A on the MSP430 is used to trigger an interrupt 250 times per second. The

ADC is sampled during each interrupt to provide the 250 Hz sampling rate required

for the ECG. Each sample is appended to a buffer dedicated to ECG data only.

Because the accelerometer only needs to be sampled at 12.5 Hz, a counter within the

interrupt ensures that the accelerometer is sampled only once every 20 interrupts,

which results in an effective sample rate of 12.5 Hz. Each time the accelerometer is

sampled, values from each axis are saved to their respective data buffers.

Because the cardiac monitor must be able to sample continuously and without

interruption, the timer interrupt must continue to operate even when data is being

written to memory. When possible, sampled data is saved directly to a primary data

buffer. When the primary data buffer is full, any additional samples are saved to the

TEMP buffer and then are returned to the DATA buffer after it has been written to

memory.

After a timer interrupt has been completed, the MSP430 enters low power mode

1, which disables the CPU and MCLK. SCLK, which is used for timer A and the

other peripheral devices, remains active. When timer A overflows, it exists low power

mode 1 and carries out the timer interrupt. Normally after such an interrupt the

MSP would return to low power mode 1. However, at this time the device is put into

active mode. In active mode, the system has a while loop that checks if data should

be written to the serial flash and/or micro SD. After data is written (if necessary),

the system re-enters low power mode 1 until the next timer interrupt.

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3.3.7 Saving Data to Serial Flash

When a STORE buffer is full, the MSP430 writes a page of data to the serial flash.

Each 256 byte flash page is broken down into a 3 byte header, 250 byte data block,

and 3 byte footer (see Figure 3-13). The header contains the 3 page address bytes

and the footer identifies the type of data block written, along with which of the two

flashes it was written to. To write a flash page, the MSP430 first checks the status

register of the flash to see if it is busy. Next, the write enable latch is set high and

the chip select is set low. The write command is passed to the serial flash along with

the 3 page address bytes (page address 0 is always 0). After the page address bytes

are sent, the header, 250 data bytes, and footer are transmitted. The MSP430 checks

the status register again until the write has completed, and then increments the page

address pointer to the next page. If the page address pointer is at the end of the

flash device, it moves to the first page of the next flash. Any data samples that were

obtained while writing to the serial flash are restored to their proper buffers. Each

type of data is written to its own page. With ECG samples of 2 bytes taken at 250

Hz, a page of ECG data will be written about twice per second. With Accel samples

of 2 bytes each taken at 12.5 Hz, three pages of Accel data (X,Y,Z) will be written

about once every 10 seconds (see Figure 3-14).

Figure 3-13: An Example Flash Block

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Figure 3-14: Data saved on flash memory.

3.3.8 Saving Data to micro SD

Once enough data has been buffered by the serial flash memory, it is written to the

micro SD card. Each write to the micro SD card requires significantly more power

than the serial flash memory, but improves with number of blocks written. The micro

SD card is written to when at least 8 pages of flash memory have saved but are not

present on the micro SD. This occurs about once every 4 seconds and corresponds

to a multi block write of at least 4 micro SD memory blocks. When the micro SD

is ready to be written to, up to 8 pages of data are read from the serial flash and

saved in the SPACE buffer. Once the SPACE buffer is full, this data is written to the

micro SD in a single write. Next, any additional data is read from the serial flash,

saved in the SPACE buffer, and written to the micro SD. If an odd number of serial

flash pages need to be written to the micro SD, the second half of the last micro SD

block is filled with a constant value that can be removed in post processing. After

the micro SD write has completed, an end of file (EOF) marker is written. When the

next write is initiated, the EOF marker is overwritten and a new one is appended to

the card.

3.3.9 Importing the data

Once the data has been saved to the micro SD card and testing is complete, it can be

read directly by a computer. The hex editor Hex Workshop [25] is used to search for

the EOF marker on the micro SD card and then all the data is saved as a binary file.

This binary file is read by a matlab script that generates data vectors corresponding

61

to each signal. The matlab script iterates through the binary file 256 bytes at a time

(i.e. one page of flash memory at a time). First, the script determines if the page of

interest is a valid page of data. If not, it either skips to the next page or terminates

depending on the contents of the header and footer. If the page is a valid data page,

the script converts the 250 data bytes into their corresponding 125 data samples. In

the case of the ECG, this involves converting the high byte and low byte into a 16 bit

number and changing from ADC code to volts. In the case of the accelerometer, the

high byte and low byte are combined, and the resulting number is converted from a

two’s complement number to a signed integer. This signed integer is then converted

into gs. When the script is finished, MATLAB automatically plots the ECG data in

one window and the 3-axis acceleration data in another.

3.4 Cardiac Monitor Specifications

This section will discuss how the cardiac monitor meets the specifications outlined in

Chapter 2. The ECG specifications will be presented first, followed by the accelerom-

eter specifications and finishing up with the system specifications.

3.4.1 ECG Specifications

Specification Target Calculated MeasuredBandwidth 0.5 – 125 Hz 0.5 – 133 Hz 0.5 – 112 Hz

Input Referred Noise < 20µVrms 3.3 µVrms 3.6 µVrms

Gain 100–1000+ 118–1770 130–1500CMRR (@ 60 Hz) 90+ dB 100 dB 99 dB

Table 3.3: ECG Signal Quality Requirements and Measurements

Specification ValueLeads 1

Electrodes 2–3ADC resolution 12 bits

Table 3.4: ECG Signal Quality Specifications by Design

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The cardiac monitor was designed to take a single ECG lead with 2 or 3 electrodes

and is sampled at 12 bits. The high pass frequency of the cardiac monitor is set by an

op amp fed into the reference pin of the instrumentation amplifier. The time constant

set by the input resistor and feedback capacitance results in a high pass corner of 0.5

Hz. The low pass corner frequency of the system is set by the inverting amplifier in

the analog front end. The actual low pass corner frequency is 112 Hz.

The input referred noise of the analog front end is calculated by considering the

following noise sources: two OPA333 input buffers, one INA333, another OPA333

acting as an inverting amplifier, and resistors connected to this inverting amplifier.

The noise from the OPA333 and associated resistors is divided by the first stage gain.

The noise of the OPA333 is 53 nV√Hz

and the noise of the INA333 is 50 nV√Hz

. The total

noise integrated over the bandwidth of 0.5 to 125 Hz (assuming a single pole roll off)

is 3.3 µVrms. The power spectral density of the output referred noise was determined

using the psd function in Matlab. Noise power was divided by the square of the

amplifier transfer function and integrated over the range of 0 Hz to 112 Hz * π/2 (to

account for single pole roll off) to determine the total RMS input referred noise of

3.6µVrms.

The gain of the system is set by 4 binary weighted resistors and, from calculations,

should range between 118 and 1770. In practice, the gain appears to be slightly less

than the calculated values. The CMRR is 99 dB, which is around what was specified

by the Instrumentation Amplifier data sheet.

3.4.2 Accelerometer Specifications

Specification ValueRange ± 8g

Resolution 12 bitsSample rate 12.5 Hz

Table 3.5: Accelerometer Signal Quality Requirements

The accelerometer specifications are easily configured using the ADXL346. It was

configured to have a range of ± 8g, with a resolution of 12 bits and a sample rate of

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12.5 Hz.

3.4.3 System Specifications

Specification Minimum Target ActualTest duration 24 hours 1+ weeks 9 – 10 days

Memory 128 MB 1+ GB 1+ GBPower dissipation < 9.7 mW < 9.7 mW < 6.6 – 7.3 mW

Table 3.6: Overall system specifications

The test duration specification is set by the minimum of the memory and the

power dissipation. It will either be memory limited or power dissipation limited. 20

ECG pages and 3 accelerometer pages are written every 10 seconds. This corresponds

to 23pages10sec∗ 256 bytes

page= 5888 bytes

10sec. For a test duration of one week, 0.33 GB of memory

is required. A micro SD card can have higher capacity than this, so the device will

be limited by its power dissipation.

To determine power dissipation, the relative contributions of the different parts of

the final algorithm need to be considered. First, the standby current of the system

was measured to be about 0.6 mA. Next, the average current was measured with the

timer interrupt enabled. This current was about 0.8 mA. The average current drawn

when only writing to the serial flash was between 1.5 mA and 3 mA. Finally, the

average current drawn when writing to the micro SD (and getting the corresponding

data from the serial flash) was between 9 mA and 10 mA.

Operation CurrentStandby 0.6 mA

Timer Interrupt 0.8 mASerial Flash Write 1.5 mA – 3 mAMicro SD Write 9 mA – 10 mA

Table 3.7: Currents drawn for different operations of the cardiac monitor.

The current drawn with the timer interrupt enabled is considered an “always

on” contribution to the overall power dissipation. To determine the contribution of

writing to the flash and writing to the micro SD, the duty cycle of such contributions

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must be determined. Writing a single page of serial flash data (with all overhead)

takes 32 ms. Each write to the micro SD card (4+ blocks, including getting data

from the micro SD and writing the EOF marker) takes 680 ms total (see Table 3.8

for the breakdown).

Operation Duration (ms)Serial Flash write 32 ms

Serial Flash read (8 pages) 408 msMicro SD write (4 blocks) 208 msMicro SD write (1 block) 64 ms

Table 3.8: Write / Read times for different operations of the cardiac monitor.

The micro SD card is written to approximately once every 4 seconds. The worst

case contribution of the flash is then:

3mA ∗ 23pages

10sec∗ 32ms

page= 3mA ∗ 73.6ms

sec= 0.22mA (3.1)

And the worst case contribution of the micro SD card is 10mA ∗ 680ms4sec

= 1.7mA.

The total average current drawn is then in the worst case 2.72 mA or 7.3 mW.

Repeating the same analysis with a current of 1.5 mA for the serial flash and 9 mA

for the micro SD results in a power dissipation of 6.6 mW. The system should be able

to run for 9 – 10 days before recharging.

65

66

Chapter 4

Clinical Test

After testing basic device functionality, the next step in validating the wearable car-

diac monitor is with a clinical test. In this chapter, a clinical test conducted at the

Clinical Research Center (CRC)1 at MIT will be presented. Motivation for the study,

the study protocol, analysis and preliminary results will be discussed.

4.1 Motivation

The motivation for the study can be broken down into four distinct goals, summarized

below.

To evaluate ECG signal quality of the cardiac monitor

To determine the comfort level of the cardiac monitor

To examine the relationship between activity levels and heart rate

To obtain a comprehensive suite of physiological signals in one data set for

future algorithm development

1This work was conducted with support from Harvard Catalyst — The Harvard Clinical andTranslational Science Center (National Center for Research Resources and the National Centerfor Advancing Translational Sciences, National Institutes of Health Award #UL1 RR 025758 andfinancial contributions from Harvard University and its affiliated academic health care centers). Thecontent is solely the responsibility of the authors and does not necessarily represent the officialviews of Harvard Catalyst, Harvard University and its affiliated academic health care centers, or theNational Institutes of Health.

67

4.1.1 ECG Signal Quality

The first goal is to evaluate the signal quality of the ECG on the cardiac monitor. The

ECG should have a clear view of the P wave, QRS complex and T wave. Modulation

of the QRS amplitude associated with respiration should be readily visible. The ECG

should be clean even during activities of high movement such as running, and should

be of at least as high quality as a currently available ECG monitor.

4.1.2 Comfort Level

The second goal of the clinical test is to evaluate the comfort level of the device. The

participants will be wearing the device while they carry out different activities. The

board should be as minimally obtrusive to the performance of the tasks. Ideally, the

participants would not even notice that they are wearing a device.

4.1.3 Activity Level

The third goal of the clinical test is to examine the relationship between activity level

(as measured by the 3-axis accelerometer) and heart rate.

4.1.4 Creating a Suite of Physiological Signals

The fourth goal of the clinical test is to obtain a comprehensive suite of physiological

signals. This suite can be used to better understand the cardiovascular system as

important signals will all be in the same, concurrent data record. Future algorithm

development could benefit from such a comprehensive suite.

4.2 Protocol

Four healthy participants ages 22 to 40 with an average age of 28.5 years were tested.

Data from all four were deemed acceptable for analysis. All subjects wore the three

electrode model in a lead II configuration (the two electrode model will be tested in

future work). A Criticare 504-US ECG recorder [26], with electrodes placed adjacent

68

to those on the cardiac monitor, was used as a comparison. Participants also wore

two respiration bands (Inductotrace [27]), a pulse oximeter (Criticare 504-US), and a

continuous blood pressure monitor (Portapres [28]) to acquire additional physiological

signals during the test. After all the devices are positioned on the participant, the

participant’s left hand is placed in a sling. This sling keeps the Portapres at the

level of the heart and helps keep some of the wires out of the way throughout the

interventions.

Figure 4-1: Participant with all the devices attached and ready to begin the clinicaltest.

The test was broken down into three different activity levels: rest, moderate, and

heavy. When possible, the participant was given a minute of stationary rest between

interventions to allow the body to return to a baseline state and re-calibrate the blood

pressure monitor. A button was pressed at the beginning and end of each intervention

(once to signal a start, twice to signal and end). Times of the corresponding button

presses were recorded on a spreadsheet by a researcher (see Figure 4-3). An overview

of the clinical test sequence and interventions can be found in Figure 4-2. The protocol

described above is conducted twice in a row (time permitting) for each participant.

Two researchers on the IRB and a nurse were required to be present for the duration

of the test. Before the test, vital statistics such as age, height, weight and blood

pressure were recorded. After the test, participants rated the comfort of the device.

Oversight for research participants was provided by Catherine Ricciardi RN, BSN

and Ravi Thadhani MD, PhD.

69

Figure 4-2: Sequence of interventions in the clinical test (run twice per partcipant).

Figure 4-3: Researcher recording the times associated with each interval.

The participant begins the test in the supine position by lying down on a hospital

bed for 5 minutes. After time has elapsed, the participant sits up quickly, rests for 1

minute, and then performs the action of sitting for 5 minutes. Finally, the participant

stands up, rests for 1 minute, and then performs the action of standing for 5 minutes.

After the participant has stood for the appropriate duration, the moderate activity

tests begin. The moderate movement phase begins with light hopping, followed by

left arm movement, and finishes with a valsalva maneuver. A valsalva maneuver is

performed by attempting to exhale against a closed airway and is used to evaluate the

autonomic nervous control of the heart. The light hopping and left arm movement

are each 1 minute in duration, with 1 minute between interventions for calibration.

The valsalva maneuever takes a total duration of 10 seconds.

The heavy activity portion of the clinical test begins with 5 minutes of walking

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on a treadmill, at a pace of no more than 4 mph. Without stopping, the speed of the

treadmill is then increased to a light jog / run at a pace of no more than 7 mph. The

participant is given 2 minutes to rest after stepping down from the treadmill. At this

point in time the participant is also offered water and given any additional time if

necessary. The last intervention is stair stepping. The participant steps up and down

off the back of the treadmill for 1 minute. After the stair stepping is complete, final

calibration of the blood pressure monitor and the protocol is complete.

Figure 4-4: Participant walking on the treadmill while the data is being monitoredon the PC.

4.3 Analysis

4.3.1 Cardiac Monitor Signal Quality

The first objective of the clinical test was to evaluate the performance of the cardiac

monitor described above. This was achieved by simultaneously recording an ECG

trace from the cardiac monitor and a device already accepted in the literature (i.e.

the Criticare recorder). We chose to compare the two ECG traces based on how each

trace performed when analyzed with a QRS detection algorithm (in this case, the

71

wqrs algorithm [29]).

The first step to compare the two ECG traces is to align the two signals in time.

The start and stop times of both traces were recorded. First, the clinical recorder data

was imported into the WaveForm Database (WFDB) format for use in Physionet’s

WAVE viewer [30]. The clinical recorder samples at 12 kHz, so the data was down-

sampled to 250 Hz. The cardiac monitor data was imported into a separate WFDB

file. While this trace is ideally sampled at the same frequency as the downsampled

clinical recorder trace, the effective sampling frequency of the cardiac monitor can

vary by about ± 1 Hz. To determine the effective sampling rate, each ECG trace’s R

waves were annotated. An R-R interval series was extracted for each trace. The two

series were plotted in matlab and aligned in time. Once the series were aligned in

time, the relative sampling rate between the two traces can be measured. For exam-

ple, if for the same beat, one trace records an R-R interval of 126 samples whereas the

other records an R-R interval of 125 samples, the effective sampling frequency can be

determined by considering that: 126x

= 125250

or x = 126125

250. With the effective sampling

frequency and relative timings between the two traces in hand, the two traces can

be aligned. In practice, dropped data from the clinical recorder prevented perfect

realignment of the two traces for the entire duration of the clinical test.

Now that the traces are time aligned, a “gold standard” set of annotations is

needed. These annotations should be the best possible representation of when a

heart beat occurred during the clinical test. The “gold standard” annotations were

created by first running the wqrs algorithm (a widely available QRS detection algo-

rithm), then manually reviewing the annotations and making corrections as needed.

The “gold standard” set of annotations were then compared with the annotations

generated by the wqrs algorithm (without any human intervention) for each trace. If

a given ECG trace is of sufficient signal quality, the QRS detection algorithm should

produce annotations in close proximity to the “gold standard” annotations. However,

if sections of the given ECG trace have inadequate signal quality, additional annota-

tions may be added, or skipped completely. An annotation from the test ECG trace

and a “gold standard” annotation are considered a match if they are found within

72

150 ms of each other.

Comparisons were made using the bxb algorithm (a beat by beat comparison al-

gorithm), which is readily available in the PhysioNet Toolkit. The bxb algorithm

takes two different sets of annotations as inputs and returns two outputs: QRS sen-

sitivity and QRS positive predictivity. QRS sensitivity is defined as the percentage

of QRS matches the wqrs algorithm found of the total number of “gold standard”

annotated beats. This is a representation of how capable the given ECG trace was of

identifying a real beat (as indicated by the “gold standard” annotation). Missing a

beat lowers this percentage. QRS positive predictivity is defined as the percentage of

correct QRS detections compared with the total number of QRS detections. This is

a representation of how reliable the given ECG trace was at identifying a real beat.

False positives lower this percentage.

4.3.2 Cardiac Monitor Comfort Level

The second objective of the clinical test was to determine how comfortable the cardiac

monitor was to wear. Each participant was asked to complete an exit survey after

testing. The survey asked how comfortable the cardiac monitor was, and asked for

written feedback about any improvements that could be made to the device.

4.4 Results

4.4.1 Cardiac Monitor Signal Quality

The QRS sensitivity and positive predictivity of the two ECG traces are summarized

in Table 4.1. Both devices performed well in almost all the interventions. The biggest

differences between the two occurred during interventions with heavier movement,

particularly running. When there was a lot of movement, the clinical recorder ECG

trace had a lot of baseline drift and a lot of noise (possibly due to motion artifacts

or the electrodes coming loose). Care was taken to ensure that the wires were as

secure as possible, but the clinical recorder appeared to be generally less reliable than

73

the cardiac monitor. In two of the four subjects, the running section on the clinical

recorder could not be properly annotated because there was so much noise. In the two

subjects where running could be annotated, the QRS sensitivity was high (95.3%).

However, the predictivity was low (24.6%)

In the first two subjects, the analog front end appears to have saturated. While

the ADC is not completely railed, a comparison of the relative amplitudes of the

P and T waves versus the QRS complex and a lack of respiration in much of the

recording suggests that the amplifier is saturated. Data comparing the two ECG

traces during running and standing can be seen in Figure 4-5 and 4-6. A trace from

the third subject that demonstrates a more appropriate scaling between the QRS

complex and the P and T waves is presented in Figure 4-7.

InterventionsQRS Sens. (mean,std) QRS Pos. Predict. (mean,std)Cardiac Clinical Cardiac Clinical

Supine 100 (0) 99.89 (0.25) 100 (0) 100 (0)Sit 99.94 (0.13) 100 (0) 100 (0) 100 (0)Stand 100 (0) 99.87 (0.30) 100 (0) 100 (0)Hop 100 (0) 95.57 (4.65) 100 (0) 69.71 (41.82)Move 99.28 (1.61) 97.26 (5.48) 99.05 (2.13) 85.41 (31.97)Valsalva 100 (0) 100 (0) 100 (0) 100 (0)Walk 100 (0) 96.31 (4.59) 100 (0) 50.19 (45.04)Run 99.18 (1.06) 54.73 (50.3) 98.93 (1.26) 26.98 (35.18)Step 100 (0) 97.18 (1.55) 100 (0) 100 (0)

Table 4.1: QRS Sensitivity and Positive Predictivity for both the Cardiac Monitorand the Clinical Recorder. All values reported are in percentages (n = 4).

4.4.2 Cardiac Monitor Comfort Level

Participants rated the cardiac monitor comfort level on a 5 point scale ranging from

very uncomfortable to very comfortable. All participants rated the cardiac monitor

either somewhat comfortable or very comfortable. In the comments, the most com-

mon complaint was about the portapres, which can be very constricting when worn

for the duration of the clinical test.

74

4.4.3 Summary

Overall, both the cardiac monitor developed in this thesis and the clinical recorder

performed well in low to moderate activity levels. However, the cardiac monitor sub-

stantially outperformed the clinical recorder under heavy activity levels, particularly

running. The clinical recorder could not reliably acquire a clean ECG while a partic-

ipant was running. When the clinical recorder was able to record a reasonably clean

ECG, the QRS sensitivity was high but the QRS positive predictivity was very low,

suggesting that there is still a lot of noise in the signal that caused false positives to

occur. This difference in reliability may have to do with the shorter wires used with

the cardiac monitor, and/or the active buffering of the electrode sites on the cardiac

monitor. Participants all rated the cardiac monitor comfort level as either somewhat

comfortable or very comfortable (4 or 5 on a scale of 5, 5 being very comfortable).

Figure 4-5: ECG of a participant while running. The output is likely saturatedbecause the P and T waves should not be that large compared to the QRS complex.

75

Figure 4-6: ECG of a participant while standing. The output is likely saturatedbecause the P and T waves should not be that large compared to the QRS complex.

Figure 4-7: ECG of a participant while supine. The QRS complex is larger relativeto the P and T waves than in previous images, suggesting that this participant hada smaller amplitude ECG.

76

Chapter 5

Conclusions

A wearable cardiac monitor has been motivated, designed and implemented. Clinical

testing on the device is underway. In this last Chapter, a discussion of the cardiac

monitor’s performance, along with ideas for future work will be presented. The thesis

will be summarized after the future work.

5.1 Discussion

While preliminary results suggest that the cardiac monitor will be a viable alternative

to existing clinical options, there are a number of things that the author has learned

during the design process to improve future revisions of the board. First, it has been

noted that one of the most sensitive parts of the system is the electrode connections.

In the first revision of the electrode board, the ring to which the electrode button was

soldered is too thin in its outer diameter and was only a single layer of PCB. The

ring pops off the PCB very easily (see Figure 5-1). This issue was resolved in the

second revision of the electrode board. While the electrode ring no longer pops off

the PCB, it has been noted that the electrode connection is very sensitive on both the

electrode and central boards. Care must be taken to ensure that the buttons are firmly

secured to the PCBs. The electrode used as a driven electrode appears to be most

sensitive. This electrode is responsible for maintaining the common mode voltage of

the system and rejecting 60 Hz interference. Without a good electrode connection,

77

motion artifacts and 60 Hz noise cannot be properly reduced by the analog front end.

Figure 5-1: A picture of the first revision of the electrode board. Note how the metalring has detached from the PCB.

Because the electrode boards were small compared with the size of the electrodes,

they were not fabricated on flexible PCBs. This proved to be a reasonable design

decision. The central boards, on the other hand, were fabricated on flexible PCBs

such that the boards could bend as the individual moved. However, after the PCBs

were populated with all the required circuit components, the boards were not capable

of bending much. It may be possible to implement future revisions of the board on

thin, but rigid PCBs to save on cost.

The memory on the cardiac monitor takes up a considerable amount of space on

the central board. While both serial flash and a micro SD card were used for buffering

and redundancy, it may be possible to eliminate the serial flash devices. The MSP430

used in the cardiac monitor does not have enough RAM to guarantee that all data

will be saved before a write, but an MSP430 with more RAM could allow the serial

flash to be eliminated. This new device would need to have at least 6 KB of RAM

available.

There were two primary usability issues with the device. The first issue is that

because the device does not transmit to a base station, there is no live feedback about

the ECG or accelerometer signal quality. The board has to be placed on the body,

run for a few seconds and stopped. Then the micro SD from the board is removed

and the data can be analyzed on the computer. A live feature with radio transmission

meant for debugging could help confirm that good signal quality will be achieved for

78

the test.

Another usability issue with the device is that a hex editor must be used to save

the data from the micro SD card. This requires additional proprietary software, and

is an extra step before the data can be imported via Matlab. The biggest advantage

of the micro SD card is that it can be read directly by a computer. Either software

should be developed to eliminate the hex editor as the middle man, or the data should

be written to the micro SD card in a computer friendly file format, such as FAT32.

Implementing FAT32, however, would require additional power, as additional micro

SD reads and writes would need to be made each time data was written to a file.

Implementing software to import the data directly into Matlab would be the lowest

power solution, with minimal overhead.

5.2 Future Work

While basic proof of concept functionality with the cardiac monitor has been shown,

further clinical testing is necessary to properly validate the device. Additional sub-

jects will be recruited for the clinical test protocol described in Chapter 4. The clinical

test will be run with at least one more participant wearing the three electrode device,

and at least 5 wearing the two electrode board. Current analysis of the two ECG

traces from the clinical test only assesses the detection of the QRS complex. Further

analysis using these traces should also analyze information from the P and T waves.

Additionally, acceleration data should be considered to relate activity level to heart

rate.

The analog front end was saturated in some of the participants of the clinical test.

The cardiac monitor was developed to have 4 bits of variable gain. In the future, an

autocalibration routine will be implemented to use this functionality to set the gain

for an individual. This autocalibration routine will be run when the device starts. It

will check to see if the signal is above a defined threshold, and if necessary, decrease

the gain. The routine should be optimized to always fill the ADC as much as possible

while preventing saturation of the amplifier.

79

The form factor of the cardiac monitor has proven to be comfortable to wear,

primarily limited by the use of the wet electrodes. Future work should investigate

the use of more comfortable electrodes, such as dry electrodes. Future work should

also evaluate the possibility of implementing a flexible PCB connector between the

central and electrode boards. Additionally, a molded cover for the PCBs could help

increase patient acceptance.

5.3 Summary

Cardiovascular disease is the leading cause of death in the United States and will

become even more of an issue as the population of the United States ages. Wearable

cardiac monitors can inform physicians about heart health trends. They provide the

physician with additional information over a standard clinical examination. In this

thesis, a wearable long term electrocardiogram (ECG) monitor was developed. This

monitor can be worn by patients recovering from cardiac events to give a physician

a better understanding of their baseline physiology, and by those at risk for cardio-

vascular disease. It can also be worn by those suspected of having an arrhythmia,

particularly one that occurs infrequently. Previous work in wearable long term mon-

itoring relied on use of a base station to transmit data (either continuous ECG or

processed data). The implementation of the cardiac monitor in this thesis is able

to record data for over one week without use of a base station. Preliminary clini-

cal results from this device suggest that it is a viable alternative to existing clinical

options.

80

Appendix A

Micro SD Code

In this Chapter, code for interfacing with the micro SD card is provided. For other

code, contact maggied at mit.edu.

A.1 Micro SD Card Header File

/*−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−

/ Low l e v e l d i s k i n t e r f a c e modlue inc l ude f i l e

/−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−*/

#ifndef DISKIO

#define READONLY 0 /* 1 : Remove wr i t e f unc t i on s */

#define USE IOCTL 1 /* 1 : Use d i s k i o c t l f u cn t i on */

#include ” i n t e g e r . h”

/* Sta tus o f Disk Functions */

typedef BYTE DSTATUS;

/* Resu l t s o f Disk Functions */

typedef enum

RES OK = 0 , /* 0 : Suc c e s s f u l */

81

RES ERROR, /* 1 : R/W Error */

RES WRPRT, /* 2 : Write Protec ted */

RES NOTRDY, /* 3 : Not Ready */

RES PARERR /* 4 : I n v a l i d Parameter */

DRESULT;

/*−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−*/

/* Proto types f o r d i s k c on t r o l f unc t i on s */

int a s s i g n d r i v e s ( int , int ) ;

DSTATUS d i s k i n i t i a l i z e (BYTE) ;

DSTATUS d i s k s t a t u s (BYTE) ;

DRESULT d i s k r e a d (BYTE, BYTE* , DWORD, BYTE) ;

#i f READONLY == 0

DRESULT d i s k w r i t e (BYTE, char* , DWORD, BYTE) ;

#endif

DRESULT d i s k i o c t l (BYTE, BYTE, void *) ;

// p r i v a t e f unc t i on s

void microSDspi In i t (void ) ;

void microSDTx (char outgoing ) ;

char microSDRx (void ) ;

char microSDTxRx (char outgoing ) ;

void microSDCSLow(void ) ;

void microSDCSHigh (void ) ;

char microSDSndCmd(unsigned char cmd , unsigned long arg ) ;

/* Disk S ta tus Bi t s (DSTATUS) */

#define STA NOINIT 0x01 /* Drive not i n i t i a l i z e d */

#define STA NODISK 0x02 /* No medium in the d r i v e */

#define STA PROTECT 0x04 /* Write p ro t e c t ed */

82

/* Command code f o r d i s k i o c t r l f u cn t i on */

/* Generic command ( de f ined f o r FatFs ) */

#define CTRL SYNC 0 /* Flush d i s k cache ( f o r wr i t e f unc t i on s ) */

#define GET SECTOR COUNT 1 /* Get media s i z e ( f o r on ly f mk f s ( ) ) */

#define GET SECTOR SIZE 2 /* Get s e c t o r s i z e ( f o r mu l t i p l e s e c t o r s i z e

( MAX SS >= 1024) ) */

#define GET BLOCK SIZE 3 /* Get erase b l o c k s i z e ( f o r on ly f mk f s ( ) )

*/

#define CTRL ERASE SECTOR 4 /* Force erased a b l o c k o f s e c t o r s ( f o r on ly

USE ERASE) */

/* Generic command */

#define CTRL POWER 5 /* Get/Set power s t a t u s */

#define CTRL LOCK 6 /* Lock/Unlock media removal */

#define CTRL EJECT 7 /* Ejec t media */

/* MMC/SDC s p e c i f i c i o c t l command */

#define MMC GET TYPE 10 /* Get card type */

#define MMC GET CSD 11 /* Get CSD */

#define MMC GET CID 12 /* Get CID */

#define MMC GET OCR 13 /* Get OCR */

#define MMC GET SDSTAT 14 /* Get SD s t a t u s */

/* ATA/CF s p e c i f i c i o c t l command */

#define ATA GET REV 20 /* Get F/W re v i s i o n */

#define ATA GET MODEL 21 /* Get model name */

#define ATA GET SN 22 /* Get s e r i a l number */

/* NAND s p e c i f i c i o c t l command */

#define NANDFORMAT 30 /* Create p h y s i c a l format */

#define DISKIO

83

#endif

A.2 Micro SD .C File

#include ”msp430f247 . h” // IMPORT YOUR OWN DEVICE SPECIFIC HEADER FILE

HERE

#include ” d i s k i o . h”

#include ” f l a s h . h”

#include ” l ed . h”

/* MMC/SD command (SPI mode) */

#define CMD0 (0) /* GO IDLE STATE */

#define CMD1 (1) /* SEND OP COND */

#define CMD8 (8) /* SEND IF COND */

#define CMD9 (9) /* SEND CSD */

#define CMD10 (10) /* SEND CID */

#define CMD12 (12) /* STOP TRANSMISSION */

#define CMD13 (13) /* SD STATUS (SDC) */

#define CMD16 (16) /* SET BLOCKLEN */

#define CMD17 (17) /* READ SINGLE BLOCK */

#define CMD18 (18) /* READ MULTIPLE BLOCK */

#define CMD23 (23) /* SET BLOCK COUNT */

#define CMD24 (24) /* WRITE BLOCK */

#define CMD25 (25) /* WRITE MULTIPLE BLOCK */

#define CMD41 (41) /* SEND OP COND (ACMD) */

#define CMD55 (55) /* APPCMD */

#define CMD58 (58) /* READOCR */

#define ACMD41 (0 x80 + 41)

#define ACMD23 (0 x80+23)

/* Card type f l a g s (CardType ) */

#define CT MMC 0x01 /* MMC ver 3 */

#define CT SD1 0x02 /* SD ver 1 */

#define CT SD2 0x04 /* SD ver 2 */

#define CT SDC (CT SD1 |CT SD2) /* SD */

84

#define CT BLOCK 0x08 /* Block addres s ing */

stat ic

DSTATUS Stat = STA NOINIT ; /* Disk s t a t u s */

stat ic

BYTE CardType ; /* b0 :MMC, b1 : SDv1 , b2 : SDv2 , b3 : Block addre s s ing */

unsigned int i =0; // used during f o r loops , e t c .

unsigned char re sponse =0; // SPI response p l a c e ho l d e r

/*−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−

Module Pr i va te Functions − DEVICE DEPENDENT! ! !

−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−*/

// CS i s P4 .7

// s e t ch ip s e l e c t low

// (Be sure to con f i gu r e GPIO e l sewhere ; I i n i t i a l i z e a l l CS f o r system

in

// main)

void microSDCSLow(void )

P4OUT &= ˜BIT7 ;

// s e t ch ip s e l e c t h igh

void microSDCSHigh (void )

P4OUT |= BIT7 ;

85

// i n i t i a l i z e SPI communication wi th the micro SD

void microSDspi In i t (void )

// Begin i n i t i a l i z a t i o n process by s e t t i n g UCSWRST

UCB1CTL1 = UCSWRST;

// I n i t i a l i z e a l l r e g i s t e r s wh i l e UCSWRST = 1

// Send data on r i s i n g edge , Clock i n a c t i v e high ,

// 8 Bit data , master mode , synchronous

UCB1CTL0 = UCCKPL | UCMSB | UCMST | UCSYNC;

UCB1CTL1 |= UCSSEL1 ; // SMCLK i s source

UCB1BR0 = 3 ; // SMCLK/3 i s the c l o c k ra t e (333 kHz )

UCB1BR1 = 0 ;

// Af ter r e g i s t e r s are se t , con f i gu r e the por t s

P5DIR |= BIT3 + BIT2 ;

P5SEL |= BIT3 + BIT2 + BIT1 ; // Enable P5 .3 as c lock , P5 .2 as MI, P5 .1

as MO

// Clear UCSWRST

UCB1CTL1 &= ˜UCSWRST;

// SPI transmi t ONLY

void microSDTx (char outgoing )

// Wait f o r the TX bu f f e r to c l e a r

while ( (UC1IFG & UCB1TXIFG) == 0) ;

// Transmit data over USCI B1

UCB1TXBUF = outgoing ;

// SPI r e c e i v e ONLY

char microSDRx (void )

86

char data = 0 ;

// Receive data over USCI B1

while ( ! ( UC1IFG & UCB1RXIFG) ) ;

data = UCB1RXBUF;

return data ;

// BOTH SPI transmi t and r e c e i v e

char microSDTxRx (char outgoing )

char data = 0 ;

// Wait f o r the TX bu f f e r to c l e a r

while ( (UC1IFG & UCB1TXIFG) == 0) ;

// Transmit data over USCI B1

UCB1TXBUF = outgoing ;

// Receive data over USCI B1

while ( ! ( UC1IFG & UCB1RXIFG) ) ;

data = UCB1RXBUF;

return data ;

int waitReady (void )

int r e t r y = 0xFFFF;

BYTE response ;

r e sponse = microSDTxRx(0xFF) ;

while ( re sponse != 0xFF)

re sponse = microSDTxRx(0xFF) ;

re t ry −−;

i f ( r e t r y == 0)

87

s e t A l l ( ) ;

return 0 ;

return 1 ;

int microSDRxData (BYTE *buf f , UINT btr )

BYTE token ;

do

token = microSDTxRx(0xFF) ;

while ( token != 0xFE) ;

do

* bu f f++ = microSDTxRx(0xFF) ;

* bu f f++ = microSDTxRx(0xFF) ;

* bu f f++ = microSDTxRx(0xFF) ;

* bu f f++ = microSDTxRx(0xFF) ;

while ( btr −= 4) ;

// dummy crc

re sponse = microSDTxRx(0xFF) ;

re sponse = microSDTxRx(0xFF) ;

return 1 ;

int microSDTxData (char *buf f , BYTE token )

int wc ;

88

// se tYe l l ow () ;

i f ( ! waitReady ( ) ) return 0 ;

microSDTx ( token ) ;

i f ( token != 0xFD)

for (wc = 0 ; wc < 512 ; wc++)

microSDTx (* bu f f++) ;

// dummy crc

re sponse = microSDTxRx(0xFF) ;

re sponse = microSDTxRx(0xFF) ;

re sponse = microSDTxRx(0xFF) ;

re sponse = microSDTxRx(0xFF) ;

i f ( ( re sponse & 0x1F) != 0x05 )

setRed ( ) ;

return 1 ;

i f ( ! waitReady ( ) ) return 0 ;

// c l rYe l l ow () ;

return 1 ;

89

// Send an SD command to the dev i c e

// SHOULD BE PLATFORM INDEPENDENT

char microSDSndCmd(unsigned char cmd , unsigned long arg )

unsigned char r e t r y = 0 ;

i f ( ! waitReady ( ) ) return RES ERROR;

microSDTx (0xFF) ; // ensure i d l e f o r at l e a s t 8 c l o c k c y c l e s

// 6 by t e command

microSDTx (cmd | 0x40 ) ; // send command , f i r s t two by t e s a lways 01

microSDTx ( arg >> 24) ; // four by t e long argument

microSDTx ( arg >> 16) ;

microSDTx ( arg >> 8) ;

microSDTx ( arg ) ;

// send CRC

// CRC only needs to be co r r e c t f o r CMD8 and CMD0

i f (cmd == CMD8)

microSDTx (0 x87 ) ;

else

microSDTx (0 x95 ) ; // CMD0 CRC

microSDTx (0xFF) ; // ensure i d l e f o r at l e a s t 8 c l o c k c y c l e s

while ( ( re sponse = microSDTxRx(0xFF) ) == 0xFF) // wai t response

i f ( r e t r y++ > 0 x f e ) break ; // time out error

90

return re sponse ;

/*−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−

Pub l i c Functions

−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−*/

/*−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−*/

/* Get Disk S ta tus */

/*−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−*/

DSTATUS d i s k s t a t u s (

BYTE drv /* Drive number (0) */

)

Stat &= ˜STA PROTECT;

return Stat ;

/*−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−*/

/* I n i t i a l i z e Disk Drive */

/*−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−*/

// NOTE: de lay c y c l e s command shou ld work f o r most MSP430

// Can comment out i f t h e r e i s a t l e a s t 1 ms a f t e r s t a r t up b e f o r e

// d i s k i n i t i a l i z a t i o n

// This f unc t i on a l s o i n i t i a l i z e s SPI

DSTATUS d i s k i n i t i a l i z e (

BYTE drv /* Phys i ca l d r i v e number (0) */

)

BYTE cmd , respx [ 4 ] ;

91

microSDspi In i t ( ) ; // i n i t i a l i z e SPI

i f ( drv ) return STA NOINIT ; /* Supports on ly s i n g l e d r i v e */

d e l a y c y c l e s (1000) ; // wai t 1 ms ( assumes 1 MHz c l o c k )

/* Send 10 sp i commands wi th card not s e l e c t e d */

for ( i =0; i <10; i++)

microSDTx (0xFF) ;

CardType = 0 ;

microSDCSLow ( ) ;

i = 100 ;

do

// send r e s e t and go i d l e command

re sponse = microSDSndCmd(CMD0, 0 ) ;

while ( re sponse !=1 && i−−) ;

i f ( re sponse != 1)

microSDCSHigh ( ) ;

return re sponse ; // CMD0 f a i l s ; re turn response and check error code

microSDCSHigh ( ) ;

// Try CMD8 to determine type o f card

microSDCSLow ( ) ;

r e sponse = microSDSndCmd(CMD8, 0x1AA) ;

92

i f ( re sponse ==1)

// SD ver s i on 2

// Get re turn va l u e s o f response R7

respx [ 0 ] = microSDTxRx(0xFF) ;

respx [ 1 ] = microSDTxRx(0xFF) ;

respx [ 2 ] = microSDTxRx(0xFF) ;

respx [ 3 ] = microSDTxRx(0xFF) ;

microSDCSHigh ( ) ;

i f ( respx [ 2 ] == 1 && respx [ 3 ] ==0xAA) // card works f o r 2.7−3.6V

// Send ACMD41 with HCS b i t

// f i r s t send CMD55 then ACMD41

for ( i = 0 ; i < 1000 ; ++i )

microSDCSLow ( ) ;

r e sponse = microSDSndCmd(CMD55, 0 ) ;

microSDCSHigh ( ) ;

i f ( re sponse <= 1)

microSDCSLow ( ) ;

r e sponse = microSDSndCmd(CMD41, 1UL << 30) ;

microSDCSHigh ( ) ;

i f ( re sponse == 0)

break ;

d e l a y c y c l e s (1000) ;

93

i f ( i < 1000)

microSDCSLow ( ) ;

r e sponse = microSDSndCmd(CMD58, 0 ) ;

respx [ 0 ] = microSDTxRx(0xFF) ;

respx [ 1 ] = microSDTxRx(0xFF) ;

respx [ 2 ] = microSDTxRx(0xFF) ;

respx [ 3 ] = microSDTxRx(0xFF) ;

microSDCSHigh ( ) ;

CardType = ( respx [ 0 ] & 0x40 ) ? CT SD2 | CT BLOCK : CT SD2 ; //

SDv2

else // SDv1 or MMCv3

i = 1000 ;

microSDCSLow ( ) ;

i f (microSDSndCmd(ACMD41, 0 ) <= 1)

CardType = CT SD1 ; cmd = ACMD41; // SDv1

else

CardType = CT MMC; cmd = CMD1; // MMCv3

microSDCSHigh ( ) ;

// wai t f o r card to l e a v e i d l e s t a t e

do

94

microSDCSLow ( ) ;

r e sponse = microSDSndCmd(cmd , 0 ) ;

microSDCSHigh ( ) ;

while ( re sponse ==1 && i−−) ;

i f ( CardType )

// INSERT CHANGE TO FAST MODE HERE

UCB1CTL1 |= UCSWRST;

UCB1BR0 = 1 ; // SMCLK i s the c l o c k ra t e (1 MHz)

// Clear UCSWRST

UCB1CTL1 &= ˜UCSWRST;

Stat &= ˜STA NOINIT ;

else

Stat |= STA NOINIT ;

return Stat ;

/*−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−*/

/* Read Sector ( s ) */

/*−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−*/

DRESULT d i s k r e a d (

BYTE drv , /* Phys i ca l d r i v e nmuber (0) */

BYTE *buf f , /* Pointer to the data b u f f e r to s t o r e read data */

95

DWORD secto r , /* S ta r t s e c t o r number (LBA) */

BYTE count /* Sector count ( 1 . . 1 28 ) */

)

DSTATUS s ;

s = d i s k s t a t u s ( drv ) ;

i f ( s & STA NOINIT) return RES NOTRDY;

i f ( ! count ) return RES PARERR;

i f ( ! ( CardType & CT BLOCK) ) s e c t o r *= 512 ; // conver t to by t e

addres se s

microSDCSLow ( ) ;

i f ( count == 1)

i f ( ( microSDSndCmd(CMD17, s e c t o r ) == 0) && microSDRxData ( buf f , 5 1 2 ) )

count = 0 ;

else

i f (microSDSndCmd(CMD18, s e c t o r ) == 0)

do

i f ( ! microSDRxData ( buf f , 512) ) break ;

bu f f += 512 ;

while (−−count ) ;

microSDSndCmd(CMD12, 0) ;

microSDTx (0xFF) ; // ex t ra c l o c k c y c l e

microSDCSHigh ( ) ;

96

return RES OK;

/*−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−*/

/* Write Sec tor ( s ) */

/*−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−*/

DRESULT d i s k w r i t e (

BYTE drv , /* Phys i ca l d r i v e number (0) */

char *buf f , /* Pointer to the data to be wr i t t en */

DWORD secto r , /* S ta r t s e c t o r number (LBA) */

BYTE count /* Sector count ( 1 . . 1 28 ) */

)

DSTATUS s ;

s = d i s k s t a t u s ( drv ) ;

i f ( s & STA NOINIT) return RES NOTRDY;

i f ( s & STA PROTECT) return RES WRPRT;

i f ( ! count ) return RES PARERR;

i f ( ! ( CardType & CT BLOCK) ) s e c t o r *= 512 ; // conver t to by t e

addre s s ing

microSDCSLow ( ) ;

microSDTx (0xFF) ;

i f ( ! waitReady ( ) ) return RES ERROR;

i f ( count == 1)

i f ( ( microSDSndCmd(CMD24, s e c t o r ) == 0) && microSDTxData ( buf f , 0xFE)

)

count = 0 ;

else

setRed ( ) ;

97

else

i f ( CardType & CT SDC) microSDSndCmd(ACMD23, count ) ;

i f (microSDSndCmd(CMD25, s e c t o r ) == 0)

do

i f ( ! microSDTxData ( buf f , 0xFC) )

setRed ( ) ;

break ;

bu f f += 512 ;

while (−−count ) ;

i f ( ! microSDTxData (0 , 0xFD) )

count = 1 ;

i f ( ! waitReady ( ) ) return RES ERROR;

microSDCSHigh ( ) ;

microSDTx (0xFF) ;

return count ? RES ERROR : RES OK;

/*−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−*/

/* Misce l l aneous Functions */

/*−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−*/

DRESULT d i s k i o c t l (

BYTE drv , /* Phys i ca l d r i v e nmuber (0) */

BYTE c t r l , /* Contro l code */

98

void * bu f f /* Buf fer to send/ r e c e i v e con t r o l data */

)

DRESULT r e s ;

switch ( c t r l )

case CTRL SYNC : /* Make sure t ha t no pending wr i t e proces s */

r e s = RES OK;

break ;

default :

r e s = RES PARERR;

r e s = RES OK;

return r e s ;

99

100

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