Computer‐aided measurement techniques
Department of Medical Informatics Faculty of MedicineUniversity of SzegedUniversity of Szeged
ComputerComputerComputer‐‐‐aided measurement techniquesaided measurement techniquesaided measurement techniques
Contents
course outlineaimsaimsstructurelecture outlinelecture outlinelaboratory practicals
measurement designelectromyographyelectrocardiographybl dblood pressure measurementrespiratory function
Computer‐aided measurement techniques
Course outline
aimsaims
To track the link between the world of the continuous analogue signals and the digital processing methods.
To address the main components of this link via the examples of typical non‐link via the examples of typical non‐invasive medical measurements.
Computer‐aided measurement techniques
Course outlinestructure
Lecture: basic module (4 hrs):Lecture: basic module (4 hrs):fundamentals and tools of measurement techniques and signal processing
Laboratory practicals (4x2 hrs):measurement task • physiological background • jointmeasurement task • physiological background • joint measurements & data acquisition
I di id l k (4 2 h )Individual work (4x2 hrs):off‐line processing of recorded data • report preparation
Seminar (2 hrs):discussion of findings • conclusions
Computer‐aided measurement techniques
Course outlineL t f d t l d t l f tLecture: fundamentals and tools of measurement techniques and signal processing
basic concepts: signals vs dataclassification of signalstransducerssignal conditioninga lisamplinganalog‐to‐digital conversion
pre‐processing in the time domainh f dpre‐processing in the frequency domain
Computer‐aided measurement techniques
Discrete (digital) data vs. continuous (analog) signals
SIGNALS:
Physical quantities changing (continuously) in time. They carry dynamic information.time. They carry dynamic information.
Examples: blood pressure recordings, ECG, EEG,Examples: blood pressure recordings, ECG, EEG, EMG, respiratory airflow and pressures.
Computer‐aided measurement techniques
Discrete (digital) data vs. continuous (analog) signals
DATA:
• Measured (numerical) values; they can be d i h i h llentered in the computer either manually or
from an “intelligent” measuring device di ldirectly.
Examples: blood gas concentrations determined from bloodExamples: blood gas concentrations determined from blood samples, readings of systolic and diastolic blood pressure valuesa ue
• Sample sequences from a (continuous) signal.p q g
Computer‐aided measurement techniques
DETERMINISTIC SIGNALS
Any future value can be predicted on the basis of past values
HARMONIC
PERIODIC
QUASI‐PERIODIC
TRANSIENT
Computer‐aided measurement techniques
NON‐DETERMINISTIC SIGNALS(random or stochastic processes)
The temporal change of the signal cannot be predicted by exact mathematical methods There are statistical means of characterizationmethods. There are statistical means of characterization.
STATIONARY
NON‐ STATIONARY(CHANGING POWER)
NON‐ STATIONARY(CHANGING MEAN)
Computer‐aided measurement techniques
CLASSIFICATION OF ANALOG SIGNALS
ANALOG
DETERMINISTIC NON-DETERMINISTIC
PERIODIC NON- STATIONARY NON-PERIODIC PERIODIC STATIONARY STATIONARY
HARMONIC QUASI-PERIODIC
GENERAL PERIODIC TRANSIENT
Computer‐aided measurement techniques
SIGNAL ACQUISITION AND PRE‐PROCESSING
CONDITIONED
ANALOGSIGNAL
TRANS‐ AMPLI‐ ANALOGA‐D DIGITALTRANS
DUCERAMPLIFIER
ANALOGFILTER
CONVER‐TER
PROCES‐SOR
ANALOGPHYSICAL DIGITALANALOGELECTRICAL
SIGNAL
PHYSICALSIGNAL
DIGITALVALUES
Computer‐aided measurement techniques
TRANSDUCERS (SENSORS)
transducer• temperature voltage
input (x) output (y)
t ti
temperature• force• pressure• velocity
voltage
y saturatione o i y• acceleration• voltageetc.
characteristics:linearity
offsetnon‐linearity
ysensitivityinput range(zero) stability
x
price
Computer‐aided measurement techniques
Shannon’s Sampling Theorem:Sampling frequency ≥ 2(max frequency)
original signal
Sampling frequency ≥ 2(max. frequency)
fs>2fmax
fs<2fmax
Computer‐aided measurement techniques
ANALOG‐DIGITAL CONVERSION
digitalvalues
sampling holding quantitizing codingq g g
011010
conditionedanalogi l
A‐D converter
signal
Computer‐aided measurement techniques
MULTICHANNEL CONVERSION
a li holdisampling holdingmultiplexeru1
A‐D converteru2
•
2
••
un
Computer‐aided measurement techniques
ANALOG‐DIGITAL CONVERSION
analog input
u>yu
y
clockinput
1 …101010…
&y
counterzeroing
digital‐analog digital…
digital analogconverter values
Uref
Computer‐aided measurement techniques
RESOLUTION OF THE A‐D CONVERSION
word length (bit) No of ranges resolution (%)word length (bit) No. of ranges resolution (%)
1 2 502 4 253 8 12.5… … …8 256 0.39110 1024 0.09812 4096 0.02416 65536 0.0015
Computer‐aided measurement techniques
Characterization of stochastic signals: amplitude distribution
200
300
200
300
(t) 0
100
rték
0
100
f
-200
-100
ér
-200
-100
t (s)
37.15 37.20 37.25 37.30 37.35-300
200
szám
0 5 10 15 20 25 30-300
200
t (s) szám
Computer‐aided measurement techniques
Course outlinestructure
Lecture: basic module (4 hrs):Lecture: basic module (4 hrs):fundamentals and tools of measurement techniques and signal processing
Laboratory practicals (4x2 hrs):measurement task • physiological background • jointmeasurement task • physiological background • joint measurements & data acquisition
I di id l k (4 2 h )Individual work (4x2 hrs):off‐line processing of recorded data • report preparation
Seminar (2 hrs):discussion of findings • conclusions
Computer‐aided measurement techniques
Course outlined f
1 electromyography (EMG)
topics and infrastructure
BIOPAC®
STUDENT LAB SYSTEM
1. electromyography (EMG)2. electrocardiography (ECG) 3 non invasive blood pressure (BP)SYSTEM 3. non‐invasive blood pressure (BP)
4 respiratory mechanics (RM)PISTON® 4. respiratory mechanics (RM)5. electroencephalography (EEG)*6. reaction time*
PISTON®
spirometry system
Wi L 7. skin galvanic response*8. respiratory cycle*9. polygraphy*
WinLung forced oscillation laboratory system p yg p y
* practicals ready for course extension
Computer‐aided measurement techniques
BIOPAC STUDENT LAB SYSTEM
Aoners
AD ‐DA
al con
diti
sensors:sign
aevaluation:
pre‐processingelectrodespressure transducersswitches
p p gtime intervalsfrequency contentcorrelation
.
.etc.
.
.etc.
Computer‐aided measurement techniques
BIOPAC STUDENT LAB SYSTEM
setting‐up: recording length & sampling
Computer‐aided measurement techniques
channel measurement boxes
channel # measurement type result
Biopac SL SYSTEMscreen
menu commands
lesson buttons
channel # measurement type resultscreen
lesson buttons
channel boxes measurement region
append markersmarker label
event markersmarker tools
lesson buttonsvertical scales
horizontal scalevertical scroll bar
horiz. scroll bar
journal tools
j l
zoom toolI‐beam cursorl ti t ljournal selection tool
Computer‐aided measurement techniques
electromyographyelectromyographyelectromyographyy g p yy g p yy g p y
electromyography
basics
Computer‐aided measurement techniques
electromyographyelectromyographyelectromyographybackground
y g p yy g p yy g p y
Skeletal muscle performs mechanicalwork.It is stimulated to contract when thebrain or spinal cord activates motor units.An action potential in the motoneuroncauses activation of muscle fibers.The activation of motor units by actionpotentials generates a stochastic voltagesignal in the muscle.gThe amount of work is proportional tothe number of activated motor units.Surface electromyography is measuresSurface electromyography is measures total muscle electrical activity via skin electrodes
Computer‐aided measurement techniques
electromyographyelectromyographyelectromyographymeasurement tasks
y g p yy g p yy g p y
t f EMG d i t i h imeasurement of EMG during stepwise changes in grip force
i f EMG i icomputation of EMG intensitycorrelation analysis between grip force and EMG activityrelationship between grip force and EMG intensity during maximum effort
Computer‐aided measurement techniques
electromyographyelectromyographyelectromyographymeasurement protocol
y g p yy g p yy g p y
Computer‐aided measurement techniques
electromyographyelectromyographyelectromyographypreprocessing
y g p yy g p yy g p y
raw EMG power smoothed EMG powerraw EMG power smoothed EMG power
Computer‐aided measurement techniques
electromyographyelectromyographyelectromyographyevaluation: plateau responses
y g p yy g p yy g p y
Computer‐aided measurement techniques
electromyographyelectromyographyelectromyographyevaluation: muscle fatigue
y g p yy g p yy g p y
tt0.50.5
Computer‐aided measurement techniques
electromyographyelectromyographyelectromyographypoints of discussion
0 7
0.8
y g p yy g p yy g p yV.s) 0.6
0.7•• submaximal effort: linear submaximal effort: linear
relationshipsrelationshipsi l ffi l ff
Eva ‐ right armEva ‐ left arm
ower (m
V
0.4
0.5 •• maximal effort: maximal effort: dysproportional EMG dysproportional EMG powerpower
EMG po
0.2
0.3•• asymmetryasymmetry•• shifted relationshipsshifted relationships
E
0 0
0.1
0.2
grip force (N)
0 10 20 30 40 50 600.0
grip force (N)
Computer‐aided measurement techniques
electromyographyelectromyographyelectromyography0.8 points of discussion
y g p yy g p yy g p yV.s) 0.6
0.7Vladim ir ‐ right armVladim ir ‐ left arm
•• submaximal effort: linear submaximal effort: linear relationshipsrelationships
wer (m
V
0.4
0.5relationshipsrelationships
•• maximal effort: maximal effort: dysproportional EMG dysproportional EMG powerpower
EMG pow
0 2
0.3
powerpower•• asymmetryasymmetry•• different slopesdifferent slopes
E
0.1
0.2
i f (N)
0 10 20 30 40 500.0
grip force (N)
Computer‐aided measurement techniques
electromyographyelectromyographyelectromyography0.6 points of discussion
y g p yy g p yy g p ymV.s)
0.4
0.5B. A. ‐ right armB. A ‐ left arm
•• nearly linear nearly linear relationshipsrelationshipsk dk d
ower (m
0.3
0.4 •• marked asymmetrymarked asymmetry•• small intersmall inter‐‐observer observer
variabilityvariability
EMG po
0.2
0 0
0.1
grip force (N)
0 10 20 30 40 50 600.0
g p ( )
Computer‐aided measurement techniques
electrocardiographyelectrocardiographyelectrocardiographyg p yg p yg p y
l d helectrocardiography
basics
Computer‐aided measurement techniques
electrocardiographyelectrocardiographyelectrocardiographyBackground Action potentials
g p yg p yg p y
Specialized pacemaker cells start the electrical sequence ofsequence of depolarization and repolarization
The electrical signal is generated by the sinoatrial (SA) node and spreads to the ventricular muscle
The electrical activities of the heart can be detected on the body surface via
f l dsurface electrodes
Computer‐aided measurement techniques
electrocardiographyelectrocardiographyelectrocardiographyBackground:
g p yg p yg p y
rhythm generator:rhythm generator:sinus node
rhythm generator: rhythm generator: polarisation polarisation ‐‐depolarisationdepolarisation
atrioventricular (AV) node conducting conducting
systemsystemHis bundle
right and left contractile cellscontractile cells
systemsystem
Tawara bundle
Purkinje fibers
Computer‐aided measurement techniques
electrocardiographyelectrocardiographyelectrocardiographyR‐R
the ECG waves
g p yg p yg p y
1.1. baselinebaseline22 P: atrialP: atrial2.2. P: atrial P: atrial
repolarisationrepolarisation3.3. QRS: ventricular QRS: ventricular
depolarisationdepolarisationdepolarisationdepolarisation4.4. SS‐‐T: ventricular T: ventricular
contractioncontraction55 T: ventricularT: ventricular
P Q
5.5. T: ventricular T: ventricular repolarisationrepolarisation
P‐QQRS
Q‐TQ‐T
Computer‐aided measurement techniques
electrocardiographyelectrocardiographyelectrocardiographyWillem Einthoven (1860 –1927)
g p yg p yg p y
( )
Professor, University of Leiden (1886)of Leiden (1886)
Nobel Prize in Medicine (1924)( )
Computer‐aided measurement techniques
electrocardiographyelectrocardiographyelectrocardiographyAugustus Desiré Waller (1856–1922)
g p yg p yg p y
Computer‐aided measurement techniques
electrocardiographyelectrocardiographyelectrocardiography
Measurement tools
g p yg p yg p y
Computer‐aided measurement techniques
electrocardiographyelectrocardiographyelectrocardiographyg p yg p yg p y
Electrode leads
Bipolar (Einthoven)The standard leads I II and IIIThe standard leads I, II and III form a triangle, from which the electrical axis of the heart can be establishedestablishedUnipolar
aVR: right handa ig aaVL: left handaVF: left leg
Computer‐aided measurement techniques
electrocardiographyelectrocardiographyelectrocardiography
l
g p yg p yg p y
Measurement tools
non‐reusable electrodescable
lifiamplifieranti‐aliasing filterAD con erterAD converter
Computer‐aided measurement techniques
electrocardiographyelectrocardiographyelectrocardiographyg p yg p yg p y
Measurement tools
The virtual ground: th t l t i lthe central terminal
Computer‐aided measurement techniques
electrocardiographyelectrocardiographyelectrocardiographysignal analysis
g p yg p yg p y
0 . 5 0
P
RT
P
R
0 . 0 0
mV
ECG P
Q
S
P
Q
4 . 4 0 4 . 6 0 4 . 8 0 5 . 0 0 5 . 2 0 5 . 4 0 5 . 6 0 5 . 8 0s e c o n d s
- 0 . 5 0S
QT intervalRR interval
display of the ECG signal at different time scalesdetermination of the characteristic time intervals (RR and QT) és and their ratio (QT/RR) t ki f th i t t h t ttracking of the instantaneous heart rate
Computer‐aided measurement techniques
electrocardiographyelectrocardiographyelectrocardiographyg p yg p yg p yheart rate dynamicsy
200.00
mean heart rates are similar in supine and sitting positionspost‐exercise heart rate decreases fast initially but does not normalise in 2 min
100.00
120.00
140.00
160.00
180.00
BP
M
Rat
e
0.00
20.00
40.00
60.00
80.00
0.50
1.00
1.50
mV
EC
G
0.00 12.80 25.60 38.40 51.20 64.00 76.80 89.60 102.40 115.20 128.00 140.80 153.60 166.40 179.20 192.00 204.80 217.60 230.40
-1.00
-0.50
0.00
Computer‐aided measurement techniques
seconds
electrocardiographyelectrocardiographyelectrocardiographysteady periods unaffected, baseline stability recovered
g p yg p yg p yPre‐processing: high‐pass
Deep breathing
0.50
1.00
VCGunfiltered
baseline stability recoveredfiltering
112.60 115.80 119.00 122.20 125.40 128.60 131.80 135.00 138.20 141.40 144.60 147.80 151.00 154.20seconds
-0.50
0.00
mEC
Deep breathing
unfiltered
0.00
0.50
1.00
mV
EC
Gf > 0.5 Hz
112.60 115.80 119.00 122.20 125.40 128.60 131.80 135.00 138.20 141.40 144.60 147.80 151.00 154.20seconds
-0.50
Deep breathing
1.00
112.60 115.80 119.00 122.20 125.40 128.60 131.80 135.00 138.20 141.40 144.60 147.80 151.00 154.20
-0.50
0.00
0.50
mV
EC
Gf > 1 Hz
112.60 115.80 119.00 122.20 125.40 128.60 131.80 135.00 138.20 141.40 144.60 147.80 151.00 154.20seconds
Computer‐aided measurement techniques
electrocardiographyelectrocardiographyelectrocardiography
Effect of low‐pass filtering smoothing without shape distortion
g p yg p yg p y
p g g p
EC
Gunfiltered
1 1 1 . 0 0 1 1 1 . 2 0 1 1 1 . 4 0 1 1 1 . 6 0 1 1 1 . 8 0 1 1 2 . 0 0 1 1 2 . 2 0 1 1 2 . 4 0 1 1 2 . 6 0
EC
Gf < 20 Hzf < 20 Hz
1 1 1 . 0 0 1 1 1 . 2 0 1 1 1 . 4 0 1 1 1 . 6 0 1 1 1 . 8 0 1 1 2 . 0 0 1 1 2 . 2 0 1 1 2 . 4 0 1 1 2 . 6 0
Computer‐aided measurement techniques
electrocardiographyelectrocardiographyelectrocardiographyg p yg p yg p y
ECG amplitude is modulated by respiration
185.00
195.00
Heart rate dynamics
125.00
135.00
145.00
155.00
165.00
175.00
BP
M
Rat
e
85.00
95.00
105.00
115.00
1 50
0.50
1.00
1.50
mV
EC
G
-1.00
-0.50
0.00
E
204.20205.00 205.80 206.60 207.40 208.20 209.00 209.80 210.60 211.40 212.20 213.00 213.80 214.60 215.40 216.20 217.00 217.80 218.60 219.40 220.20 221.00 221.80 222.60 223.40 224.20 225.00 225.80 226.60seconds
Computer‐aided measurement techniques
electrocardiographyelectrocardiographyelectrocardiographyboth ECG amplitude and heart rate are modulated by breathingHeart rate dynamics
g p yg p yg p y
After sitting u
165.00
175.00
185.00
are modulated by breathingy
115.00
125.00
135.00
145.00
155.00
BP
M
Rat
e
85.00
95.00
105.00
2.00
0.50
1.00
1.50
mV
EC
G
30.40 32.00 33.60 35.20 36.80 38.40 40.00 41.60 43.20 44.80 46.40 48.00 49.60 51.20 52.80 54.40 56.00 57.60 59.20 60.80seconds
-1.00
-0.50
0.00
Computer‐aided measurement techniques
electrocardiographyelectrocardiographyelectrocardiographyrespiration changes the length of the isoelecticECG h t t d i
g p yg p yg p y
length of the isoelectic intervalECG: heart rate dynamics
0.50
mV
0.00
-0.50
Q ‐ TQ ‐ T
90.80 91.00 91.20 91.40 91.60 91.80 92.00 92.20 92.40 92.60 92.80 93.00 93.20 93.40 93.60dseconds
Computer‐aided measurement techniques
electrocardiographyelectrocardiographyelectrocardiographyHeart rate dynamics
g p yg p yg p yQ‐T shortening and recovery
Q ‐ T0 . 5 0
1 . 0 0
rest
1 1 2 . 6 0 1 1 2 . 8 0 1 1 3 . 0 0 1 1 3 . 2 0 1 1 3 . 4 0 1 1 3 . 6 0 1 1 3 . 8 0 1 1 4 . 0 0 1 1 4 . 2 0 1 1 4 . 4 0s e c o n d s
- 0 . 5 0
0 . 0 0
mV
EC
G
1 . 0 0
0 . 0 0
0 . 5 0
mV
EC
G10 s
R‐R and Q‐T intervalsshorten
1 4 7 . 8 0 1 4 8 . 0 0 1 4 8 . 2 0 1 4 8 . 4 0 1 4 8 . 6 0 1 4 8 . 8 0 1 4 9 . 0 0 1 4 9 . 2 0 1 4 9 . 4 0 1 4 9 . 6 0s e c o n d s
- 0 . 5 0
0 . 5 0
1 . 0 0
post‐exercise
R‐R interval still elevated
2 2 3 . 4 0 2 2 3 . 6 0 2 2 3 . 8 0 2 2 4 . 0 0 2 2 4 . 2 0 2 2 4 . 4 0 2 2 4 . 6 0 2 2 4 . 8 0 2 2 5 . 0 0 2 2 5 . 2 0
- 0 . 5 0
0 . 0 0
mV
EC
G
100 s
post‐exercises e c o n d s
Computer‐aided measurement techniques
electrocardiographyelectrocardiographyelectrocardiography
Poi t of di u ioPoi t of di u io
g p yg p yg p y
Why was the ECG baseline less stable after the exercise than before?
Points of discussion:Points of discussion:
Why was the ECG baseline less stable after the exercise than before?
Heart rate did not return to the resting level in 2 min after the exercise. H l i d hi k ld b d d f l ?How long time do you think would be needed for a complete recovery?
High‐pass filtering can restore the baseline stability of a recording that g p g y gincludes low‐frequency fluctuations, but it must not change the ECG waveform. What (high‐pass) corner frequency (in Hz) would you set if the minimum heart rate in the recording is 70/min?the minimum heart rate in the recording is 70/min?
Computer‐aided measurement techniques
blood pressure measurementblood pressure measurementblood pressure measurement
non‐invasive measurement of blood pressure
basicsbasics
Computer‐aided measurement techniques
blood pressure measurementblood pressure measurementblood pressure measurementINDIRECT MEASUREMENT OF SYSTEMIC BLOOD PRESSURE
arrangement of the auscultation method
Riva-Rocci, 1896Korotkoff, 1905
Computer‐aided measurement techniques
blood pressure measurementblood pressure measurementblood pressure measurementINDIRECT MEASUREMENT OF SYSTEMIC BLOOD PRESSURE
PRINCIPLE: comparison of cuff pressure, Korotkoff sounds and ECG
Nikolai Sergeievich Korotkoff
Computer‐aided measurement techniques
blood pressure measurementblood pressure measurementblood pressure measurementmechanisms of the Korotkoff sounds
cavitation theory
vessel wall stretch htheory
turbulenceother theoriesother theoriescombinations
Computer‐aided measurement techniques
blood pressure measurementblood pressure measurementblood pressure measurementIDENTIFICATION OF THE KOROTKOFF SOUNDS
75.00
125.00
175.00
25.00
0.98
1.95
off S
ound
s) first sound last sound
-1.95
-0.98
0.00 mV
Ste
thos
cope
(Kor
otko
0 50artefacts
0 25
0.00
0.25
0.50
mV
EC
G (.
5 - 3
5 H
z)
0.00 10.02 20.03 30.05s econds
-0.50
-0.25
Computer‐aided measurement techniques
blood pressure measurementblood pressure measurementblood pressure measurement
SYSTOLIC, MEAN AND DIASTOLIC PRESSURES
pressure (mmHg)
systolic (SBP)systolic (SBP)
A1mean (MAP)
PP
diastolic (DBP)A2
( )
t i l (MAP)mean arterial pressure (MAP):
MAP=DSP+PP/3pulse pressure (PP):
time (s)(A1≈A2)PP=SBP‐DBP
Computer‐aided measurement techniques
blood pressure measurementblood pressure measurementblood pressure measurementKOROTKOFF SOUNDS AND THE ECG CYCLE
110.56
113.32
116.08
cuff pressure
107.79
0 98
1.95ds
)
-0.98
0.00
0.98
mV
Ste
thos
cope
(Kor
otko
ff S
ound
sound
-1.95
0.25
0.50
V
35 H
z)
ECG
R
19.18 19.65 20.11seconds
-0.50
-0.25
0.00 mV
EC
G (.
5 - ECG Q
ST
Computer‐aided measurement techniques
blood pressure measurementblood pressure measurementblood pressure measurementpppstudy arrangement
BIOPAC STUDENT LAB SYSTEMBIOPAC STUDENT LAB SYSTEM
35MP3
Pcuff
micEKG
Computer‐aided measurement techniques
blood pressure measurementblood pressure measurementblood pressure measurementrecordings: cuff pressure – stethoscope sound ‐ ECG
Computer‐aided measurement techniques
blood pressure measurementblood pressure measurementblood pressure measurement
identification of the Korokoff sounds and artifacts
?? ?
Computer‐aided measurement techniques
blood pressure measurementblood pressure measurementblood pressure measurement
auditory vs visual identification of the Korokoff sounds
Computer‐aided measurement techniques
blood pressure measurementblood pressure measurementblood pressure measurementthe oscillometric principle maximum pulse pressure=mean arterial pressure
cuff pressure
stethoscope soundsound
ECG
pulse pressureextrapolation? extrapolation?
Computer‐aided measurement techniques
blood pressure measurementblood pressure measurementblood pressure measurementcomparison of the routine measurements with the computer evaluations: semiautomatic vs BIOPAC
130
140
Right 1Right 2
90
p
mm
Hg 120
130 Right 2Right 3Left 1Left 2Left 3 m
mH
g
70
80
P (s
emia
ut)
100
110Left 3
P (s
emia
ut)
60
70
SBP
80
90 DBP
50
SBP (BIOPAC) mmHg
70 80 90 100 110 120 130 14070
DBP (BIOPAC) mmHg
40 50 60 70 80 9040
Computer‐aided measurement techniques
blood pressure measurementblood pressure measurementblood pressure measurementcomparison of the routine measurements with the computer evaluations: wrist vs BIOPACp
130
14090
mH
g 120
130
mH
g
70
80
BP (w
rist)
m
100
110
BP (w
rist)
m
60
70
Right 1Ri ht 2SB
80
90 DB
40
50Right 2Right 3Left 1Left 2Left 3
SBP (BIOPAC) mmHg
70 80 90 100 110 120 130 14070
DBP (BIOPAC) mmHg
30 40 50 60 70 80 9030
Left 3
Computer‐aided measurement techniques
( ) g ( ) g
blood pressure measurementblood pressure measurementblood pressure measurementcomparison of the routine measurements with the computer evaluations: auscultation vs BIOPACp
130
140
Right 1 90
mm
Hg 120
130 Right 2Right 3Left 1Left 2Left 3 m
mH
g
70
80
P (a
uscu
lt) m
100
110Left 3
P (a
uscu
lt) m
60
70
SBP
80
90 DBP
40
50
SBP (BIOPAC) mmHg
70 80 90 100 110 120 130 14070
DBP (BIOPAC) mmHg
30 40 50 60 70 80 9030
Computer‐aided measurement techniques
( ) g ( ) g
blood pressure measurementblood pressure measurementblood pressure measurement
points of discussion:
• effects of atherosclerosis• persistence of sounds below DBP• the mercury columnthe mercury column• aneroid barometers• finger photoplethysmography• finger photoplethysmography• upper arm – wrist ‐ finger• oscillometry• oscillometry
Computer‐aided measurement techniques
respiratory functionrespiratory functionrespiratory function
spirometry and oscillationspirometry and oscillation mechanics
basicsbasics
Computer‐aided measurement techniques
respiratory functionrespiratory functionrespiratory functionSpirometer types
Menzies spirometer (1790)
Water seal cylinder spirometer
Bellows spirometer
Computer‐aided measurement techniques
respiratory functionrespiratory functionrespiratory functionquasistatic lung volumes
a
TV
IRV
TLCVC
max
TVERVRV0
FRC
V
TV tid l lTV: tidal volumeIRV: inspiratory reserve volumeERV: expiratory reserve volumeRV: residual volume
FRC: functional residual capacityVC: vital capacityTLC: total lung capacity
Computer‐aided measurement techniques
RV: residual volume
respiratory functionrespiratory functionrespiratory functionforced expiratory flow‐volume loop
fl
expiration
flow
task: expiration of
inspiration volume
task: expiration of the maximum possible volume of the forcedof the forced expiratory vital capacity (FVC) in th 1 t dthe 1st second (FEV1)
Computer‐aided measurement techniques
respiratory functionrespiratory functionrespiratory function
the pneumotachographthe pneumotachograph
Fl (Vʹ) i d th d•Flow (Vʹ) is measured as the pressure drop across a fine metal or plastic screen
•In the laminar regime, the pressure drop is proportional to flow (Hagen‐Poiseuille law)
•Volume is obtained via integration of the flow signal
Computer‐aided measurement techniques
respiratory functionrespiratory functionrespiratory function
the simple model of respiratory mechanics – the resistance
mechanical analoguemechanical analogue
electrical analogueg
Computer‐aided measurement techniques
respiratory functionrespiratory functionrespiratory function
the simple model of respiratory mechanics – the inertance
mechanical analogue
electrical analogue
Computer‐aided measurement techniques
respiratory functionrespiratory functionrespiratory function
the simple model of respiratory mechanics – the elastance
mechanical analogue
electrical analogue
Computer‐aided measurement techniques
respiratory functionrespiratory functionrespiratory functionthe simple 3‐parameter model of respiratory mechanics
R (resistance)
di i ti
X (reactance)
energy dissipationresistance
energy storageinertanceelastance
frequency
Computer‐aided measurement techniques
respiratory functionrespiratory functionrespiratory functionbroad‐band impedance of the respiratory system
Computer‐aided measurement techniques
respiratory functionrespiratory functionrespiratory function3‐parameter evaluation of respiratory impedance
measured mean and SDmodel fitting
resonance
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Computer‐aided measurement techniques
respiratory functionrespiratory functionrespiratory function3‐parameter evaluation of respiratory impedance
F%: mean fitting errorRaw: airway resistance (hPa s/l)Raw: airway resistance (hPa.s/l)Iaw: inertance (hPa.s2/l)H: elastance (hPa/l)
resonance frequency:
fRES = (1/2π) √(H/Iaw)
Computer‐aided measurement techniques
respiratory functionrespiratory functionrespiratory functionuse of reference values for spirometry and mechanicsmechanics
normal values established in a large population
statistical relationships describing the dependence on height a i i a e a io ip e i i g e epe e e o eig(H), age (A) and body weight (W), for both genders
e g the predicted value of Raw (Raw*) for females:e.g. the predicted value of Raw (Raw ) for females:
Raw*[hPa.s/l] = 9,051 – 0,0542∙H[cm] + 0,0105∙A[yr] + 0,0369∙W[kg]
if H=160 cm, A=20 yr and W=55 kg, Raw*=2,62 hPa.s/l
Computer‐aided measurement techniques
respiratory functionrespiratory functionrespiratory function
Points of discussion:Points of discussion:
• relationship between quasi‐static and forced expiratory vital capacity
• measures of reproducibility• errors in model fitting• errors in model fitting• interdependence of lung volumes and
mechanical parametersmechanical parameters
Computer‐aided measurement techniques
respiratory functionrespiratory functionrespiratory function
spirometry and oscillationspirometry and oscillation mechanics
basicsbasics
Computer‐aided measurement techniques