基於血管彈力波及脈衝傳遞時間之多變參數建立血
壓估算法
Development of a Blood Pressure Estimation Based
on Femoral Artery Elasticity Wave and Pulse
Transit Time Parameters
Adviser: Huang Ji-Jer
Presenter:Syu Hao-Yi
Date:2014/03/12
OUTLINE
1. Introduction
1. Brief introduction
2. ECG, PPG ,FET background and principles
3. Research on motivation and purpose
2. Paper Review
3. Materials and Methods
1.
2.
3.
4.
5.
6.
7.
8.
Sensor application
Analog circuits
Signal processing
Digital Circuits
GUI
Parameter definition
Software flowchart
Regression analysis and estimation of blood pressure
OUTLINE
4. Results and Discussion
1.
2.
3.
4.
5.
6.
7.
Analog circuit analysis and measurement
Digital filtering assessment and actual measurements
Digital filtering results built on firmware
Verification system
NI/LabWindows GUI
Auto gain control setting
Experiments
5. Conclusions and Future Work
1.INTRODUCTION
INTRODUCTION
• Brief introduction
– Health promotion and fertility decline in mainly reason for
the problem of an aging population
– An international reach 7% of the population aged 65 is an
aging , 14% called for aged, 20% called for super-aged
出處:行政院經濟建設委員會人力規劃處101年7月23日
1.INTRODUCTION
INTRODUCTION
• Brief introduction
– Cardiovascular defects and disease caused by diet
on life
出處:行政院衛生署
1.INTRODUCTION
INTRODUCTION
• Brief introduction
– Growing population, chronic diseases and
functional disorders are increasing, except for
medical services ,the home care services have been
our needs
Photo Source : http://www.2cm.com.tw/zoomin_content.asp?sn=0912020016
1.INTRODUCTION
INTRODUCTION
• ECG, PPG ,FET background and principles
– ECG records the heart in nerve conduction arising
from potential changes graphics
– Potential change of the heart begins with the
rhythm generator of sinoatrial node (SA node)
Photo Source : http://www.bostonscientific.com/lifebeat-online/heart-smart/electrical-system.html
1.INTRODUCTION
INTRODUCTION
• ECG, PPG ,FET background and principles
– The electrocardiogram (ECG) or
elektrokardiogramm (EKG) is a medical standard
for testing the human heart for defects and
diseases
– The typical amplitude of the R wave of the ECG
signal is approximately 1 mV
1.INTRODUCTION
INTRODUCTION
• ECG, PPG ,FET background and principles
– A photoplethysmograph (PPG) the use of light
source to measure the blood volume change of the
blood vessel
– Each ECG signal cycle corresponds to a PPG
signal
Photo Source :
INVESTIGATION OF NEW ELECTRO - OPTICAL TECHNIQUES FOR MONITORING PATIENTS WITH COMPROMISED PERIPHERAL
PERFUSION IN ANAESTHESIA
1.INTRODUCTION
INTRODUCTION
• ECG, PPG ,FET background and principles
– PPG signal amplitude with the blood out of the
tissue will be directly proportional to the change
Photo Source :
INVESTIGATION OF NEW ELECTRO - OPTICAL TECHNIQUES FOR MONITORING PATIENTS WITH COMPROMISED PERIPHERAL
PERFUSION IN ANAESTHESIA
1.INTRODUCTION
• ECG, PPG ,FET background and principles
– FET(Femoral artery elasticity wave)
1.INTRODUCTION
• Research on motivation and purpose
– Capture ECG 、PPG 、 FET signal
characteristics(PAT、HR、TDB、FET) estimate
blood pressure
•ECG
•PPG
•FET
The Circuits
of Amp. Gain
Offset
and ADC
NI/LabWindows
GUI and AGC
setting 、data save
Regression
analysis and
estimation of
blood pressure
2.PAPER REVIEW
• Continuous and non-invasive blood
pressure measurement methods
– Tonometric Method
– Vascular Unloading Method
– Pulse Transit Time
2.PAPER REVIEW
• Comparison of continuous blood pressure
measurement
壓張式血 血管無 脈 衝 到 脈 衝 到 達 時 間 恆 壓 血壓之動
壓量測
負載法
達時間
間歇性校正
低壓
態低壓量
測
動 作 雜
●
◎
◎
●
●
●
收縮壓
●
●
●
●
●
●
舒張壓
●
●
●
●
●
平均壓
●
●
●
●
●
訊
動 態 連
●
●
●
●
續
操 作 方
●
便
●:符合
◎:部分符合
●
2.PAPER REVIEW
• Long-term monitoring topics for various
applications about unconstrained or noncontact measurement of physiological
signals
–
–
–
–
Mobile
Bed
Chair
Toilet
2.PAPER REVIEW
• A Preliminary Study for Unconstrained
Pulse Arrival Time (PAT) Measurement on
a Chair
– Proceedings of the 2005 IEEEEngineering in Medicine and Biology 27th
Annual Conference Shanghai, China, September 1-4, 2005
– Ko Keun Kim1, Youngjoon Chee1, Juwan Park1, Jungsoo Kim1, Yong Kyu
Lim1, and Kwang Suk Park2
2.PAPER REVIEW
• In this paper, the correlation between the
typical PAT and the unconstrained PATs (APATs) are compared
• A-PATs: A-PATs were
measured from the
pressure pulse of the
air cushion (APP)
2.PAPER REVIEW
• To validate the correlation with typical PAT,
the three feature points was used for the A-PAT
as follows: 1) the first minimum point of the
APP, 2) the zero crossing point of the APP, and
3) the steepest descent point of the APP
2.PAPER REVIEW
• A Smart Health Monitoring Chair for
Nonintrusive Measurement of Biological
Signals
– Hyun Jae Baek, Gih Sung Chung, Ko Keun Kim, and Kwang Suk Park, Senior
Member, IEEE
– IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN
BIOMEDICINE, VOL. 16, NO. 1, JANUARY 2012
2.PAPER REVIEW
• PAT was substituted by RJ interval(RJI),
defined as the time interval from ECG R peak
to BCG J peak
2.PAPER
REVIEW
PAPER REVIEW1
• Effect of confounding factors on blood
pressure estimation using pulse arrival time
– This article has been downloaded from IOPscience. Please scroll down to see
the full text article.2008 Physiol. Meas. 29 615
– (http://iopscience.iop.org/0967-3334/29/5/007)
– Jung Soo Kim, Ko Keun Kim, Hyun Jae Baek and Kwang Suk Park
2.PAPER REVIEW
2.PAPER REVIEW
• Enhancing the estimation of blood pressure
using pulse arrival time and two
confounding factors
– This article has been downloaded from IOPscience. Please scroll down to see
the full text article.2010 Physiol. Meas. 31 145
– (http://iopscience.iop.org/0967-3334/31/2/002)
– Hyun Jae Baek, Ko Keun Kim, Jung Soo Kim, Boreom Lee and Kwang Suk
Park
2.PAPER REVIEW
• Methods
– Clinical data from dental anesthesia
– Data from unconstrained biological signal
a) Application
on a toilet seat
measurement
systems
b) Application in a vehicle
c) Application at a computer
2.PAPER REVIEW
REVIEW2
• Results()
– BP=a+b*PAT
– BP=a+b*PAT+c*HR*d*TDB
Performance enhancement for BP estimation by inclusion of confounding
factors in clinical data under dental anesthesia.
Performance enhancement for BP estimation by inclusion of confounding factors in the
unconstrained data.
3.Materials and Methods
• PPG sensor
– Reflective Optical Sensor with Transistor Output
– The CNY70 is a reflective sensor that includes an
infrared emitter and phototransistor in a leaded
package which blocks visible light
•Detector type: phototransistor
• Dimensions (L x W x H in mm): 7 x 7 x 6
• Peak operating distance: < 0.5 mm
•Typical output current under test: IC = 1 mA
• Emitter wavelength: 950 nm
• Daylight blocking filter
3.Materials and Methods
• ECG&FET Sensor
– SCC Series pressure sensors
–
–
–
–
0...5 to 0...100 psi
Low cost sensor element
Internal temperature compensation
Differential, gage and absolute
– Disposable ECG electrodes pads
3.Materials and Methods
• Analog circuits
– ECG,PPG and FET block diagram of the
measurement circuit
ECG
3.Materials and Methods
LP Filter(100Hz)
HP Filter(0.5Hz)
AGC
Notch(60Hz)
PPG
ECG-RA
FET
ECG-RL
LP Filter(22Hz)
AGC
Notch(60Hz)
FET
LP Filter(100Hz)
HP Filter(0.5Hz)
Notch(60Hz)
AGC
Microprocessor
PPG&ECG
-LA
3.Materials and Methods
• Analog circuit
– ECG、FET second-order high-pass circuit
H
f
(S )

S
2
Gs
2
 S  
2
1

ch
2 R3 * R 4 * C1* C 2
3.Materials and Methods
• Analog circuit
– ECG、PPG、FET second-order low-pass circuit
H
f
(S )

S
2
Gs
2
 S  
2
1

cl
2 R3 * R 4 * C1* C 2
3.Materials and Methods
• Analog circuit
– ECG、PPG、FET notch filter circuit
H
f
(S )

S
2
Gs
2
 S  
2
1

cn
2 R3 * R 4 * C1* C 2
3.Materials and Methods
• Analog circuits
– Auto gain control block diagram
Latch
8bit
MSP430
4bit
Offset
Analog Signal
Gain
Gain
Voffset
4051
R25
0 12 3 4 5 6 7
4051
0 12 3 4 5 6 7
…………
G6
G5
G4
Rg G7
Offset
…………
G2
G1
G0
RmG3
4bit
R51
R48
R50
OP
R24
Vf
OP
R47
Vin
R60
OP
R49
R61
Differential Amplifier
inverting amplifier
OP
Output
inverting amplifier
3.Materials and Methods
• Analog circuits
– Offset circuits
Rm  R 47
R 48
) * (5))  (
* (5)) 式1
R 48  Rm  R 47
R 48  Rm  R 47
Rm  150
100
Vf  ((
) * (5))  ((
) * (5)) 式2
100  Rm  60
100  Rm  60
Vf  ((
R 61
R51
(1 
) 式3
R 49  R 61
R50
R51
Vo2  
Voff 式4
R50
R 61
R50  R51  R51
Vo  Vo1  Vo2  Vin
*

Voff 式5
R 49  R 61
R50
R50
R 61
R51
R51

Vin 
Voff 
(Vin  Vf ) 式6
R50
R50
R50
Vo1  Vin
3.Materials and Methods
• Analog circuits
– Offset circuits
Rm/ ohm
準位調整
24k
0.4347
30k
0.2631
36k
0.1020
40k
0.0000
47k
-0.1690
51k
-0.2606
56k
-0.3703
62k
-0.4954
3.Materials and Methods
• Analog circuits
– Gain circuits
R 25
Rg
) * (
)
R 24
R 60
5k
Rg
Vgain  Voffset * ( 
) * (
)
10k
1k
Vgain  Voffset * ( 
Rg/ohm
1k
3k
6k
10k
15k
20k
51k
100k
倍率
0.1
0.3
0.6
1
1.5
2
5.1
10
3.Materials and Methods
• Signal processing
– Type Cascade form and Direct form Butterworth
design a five order low-pass filter five order highpass filter and notch filter
– High-pass cut-off frequency (fc) of 0.5Hz to
eliminate baseline drift
– 60Hz stop-band filter (Notch) to filter out noise in
utility power
3.Materials and Methods
• Signal processing
– Filter system transfer function
M
H ( z) 
m
b
z
m
m 0
N
a z
n 0
n
b0  b1 z 1      bM z M

1  a1 z 1      a N z  N
n
M
N
k 0
k 1
y (n)   bk x[n  k ]   a k y[n  k ]
3.Materials and Methods
• Signal processing
– Direct form structure diagram
3.Materials and Methods
• Signal processing
– Cascade form
y1[n]
y 2 [ n]
x[n ]
H1[ z]
H 2[ z]
.....
y[n]
H Ns [z ]
– Signal processing sub-process calculates its output
into the relationship
wk [n]  yk 1[n]  a1k wk [n  1]  a2k wk [n  2]
yk [n]  b0k wk [n]  b1k wk [n  1]  b2k wk [n  2]
3.Materials and Methods
• Signal processing
– Cascade form structure diagram
yk 1[n]
1
wk [n]
 a1k
Z-1
 a2 k
Z-1
b0 k
b1k
b2 k
yk [n]
3.Materials and Methods
• Signal processing
– High pass and low pass 5 order、notch in Matlab
filter before in Matlab
filter after in Matlab
3.Materials and Methods
• Signal processing
– Multi-scale Mathematical Morphology (3M filter),
based on set operations, provides a way to analyze
signals using nonlinear signal processing operators
that incorporate the geometry information of the
signal
3.Materials and Methods
• Signal processing
– The shape information of the signal is extracted by
using a structure element to operate on the signal,
such operators serve two purposes, i.e. extracting
the useful signal and removing the artifacts
3.Materials and Methods
• Signal processing
– 3M Filter related equations
Dilation : f  g (n)  (max
i ) (( f ( n  i )  g (i ))
Erosion : fg (n)  (min
i ) (( f ( n  i )  g (i ))
Opening : f  g (n)  f  g (g )( n)
Clo sin g : f * g (n)  fg ( g )( n)
3.Materials and Methods
• Signal processing
– In this stage, the 3M filter used to eliminate
baseline drift and reduce interference noises
(motion artifacts, muscle contraction)
3.Materials and Methods
• Signal processing
– PPG signal, PPG 1st derivative, PPG 2nd
derivative, and the process of peak detection
3.Materials and Methods
• Signal processing
– Find out 1st derivative local maxima
– To find zero-crossing point
PPG
st
PPG 1 derivative local maxima
nd
PPG 2 derivative local maxima
,crossing zero
3.Materials and Methods
• Digital Circuits
– BP estimates System Architecture
Physiological
signal
AGC
AGC
MSP430F5438A
A/D
12bit
DSP(Filter
、AGC)
DSP
UART
NI/LabWindows
GUI
Matlab GUI&
Analysis，SPSS
3.Materials and Methods
• Digital Circuits
– Firmware Flowchart
Stat
Intialization
a.Port b.timer
c.ADC
AGC
Notch
HP 5 order
LP 5 order
Interface
END
3.Materials and Methods
• GUI
– National Instruments/LabWindow CVI 9.0
訊號顯示
RS232設定
資料儲存
增益與準位調整
3.Materials and Methods
• Blood pressure parameter definition
–
–
–
–
PAT:Pulse arrive time
HR:RRinterval
TDB:Arterial stiffness index
FET: femoral artery elastic wave time parameters
HR
PAT
TDB
FET
3.Materials and Methods
• Software flowchart
– Matlab GUI
Stat
Detrend
Filter(LP、
HP、
Notch)
Normalize
Peak
detector
• Regression analysis and estimation of blood
pressure
– SPSS
– About the correlation between the legs
– BP = a + b * PAT + c * HR + d * TDB + e * FET
END
4. Results and Discussion
• Analog circuit analysis and measurement
– ECG High pass filter
– PSpice circuit simulation frequency response
fch 
1
 0.53Hz
2 10k *10k * 30 * 30
4. Results and Discussion
• Analog circuit analysis and measurement
– ECG Actual measuring high-pass circuit Bode
fch:0.58Hz
4. Results and Discussion
• Analog circuit analysis and measurement
– ECG Low pass filter
– PSpice circuit simulation frequency response
fcl 
2
1
 104.07 Hz
510 * 510 * 3 * 3
4. Results and Discussion
• Analog circuit analysis and measurement
– ECG Actual measuring low-pass circuit Bode
fcl:86.7Hz
4. Results and Discussion
• Analog circuit analysis and measurement
– ECG Notch filter
– PSpice circuit simulation frequency response
1
fcn 
 61.21Hz
2 * 26k * 0.1
4. Results and Discussion
• Analog circuit analysis and measurement
– ECG Actual measuring notch circuit Bode
4. Results and Discussion
• Analog circuit analysis and measurement
– PPG Low pass filter
– PSpice circuit simulation frequency response
fcl 
2
1
 22.96 Hz
2.1k * 2.1k * 3.3 * 3.3
4. Results and Discussion
• Analog circuit analysis and measurement
– PPG Actual measuring low-pass circuit Bode
fcl:27.1Hz
4. Results and Discussion
• Analog circuit analysis and measurement
– PPGG Notch filter
– PSpice circuit simulation frequency response
1
fcn 
 61.21Hz
2 * 26k * 0.1
4. Results and Discussion
• Analog circuit analysis and measurement
– PPG Actual measuring notch circuit Bode
4. Results and Discussion
• Analog circuit analysis and measurement
– The actual circuit diagram
ECG
FET(R)
FET(L)
PPG
Main board
4. Results and Discussion
• Digital filtering assessment and actual
measurements
– In the rear of the system analyzed using 3M filter
to eliminate baseline measurements obtained with
ECG and PPG signals
Determine structural elements
4. Results and Discussion
• Signal filtering results with R-wave detection
式5
4. Results and Discussion
• Digital filtering assessment and actual
measurements
– In the better than part of 3M filter eliminates
baseline IIR filter
P[1,  2] 
2
 Ponesided ( )d,0  1   2  
1
0Hz
0~0.5Hz 0.5~45Hz
(watts/he (watts/hertz) (watts/her
rtz)
tz)
IIR 0.00073 0.1660000 0.690046
Filter 23
6
3M 0.30950
Filter 00
0.0480000 0.052909
3
4. Results and Discussion
• Digital filtering results built on firmware
1ms
4. Results and Discussion
• Digital filtering results built on firmware
Filter before in Matlab
Filter after in Matlab
Filter after in MCU
4. Results and Discussion
• Verification system
– Contact measurement ECG compared with
commercially available instruments
4. Results and Discussion
• NI/LabWindows GUI
4. Results and Discussion
• Auto gain control setting
– Gain and offset adjustment
0.1x
0.3x
0.6x
1.0x
4. Results and Discussion
• Summary
– Sensors application and analog circuit design
– Filter circuit
– Offset and Gain
– AGC circuit
– Signal processing and firmware build
– IIR Filter
– 3M Filter
– NI/LabWindows GUI
– Waveform display
– AGC Adjustment
– Data storage
4. Results and Discussion
• Experiments
– Four waveform measurement system
– Signal feature extraction
4. Results and Discussion
• Experiments
– BP estimation parameters analysis
4. Results and Discussion
• Experiments(FET correlation between the
legs)
– About the correlation between the legs
– FET accounted for HR time proportion
System
Initial
系統量測(R-peak、FET(R)-peak、
FET(L)-peak)
Over
3min
HR
FET
4. Results and Discussion
• Experiments(FET correlation between the legs)
– Total : ECG 、FET(R)、FET(L) peak number
– Se : success rate
– Corr : FET correlation between left and right legs
Time
Total(bea True(b
ts)
eats)
Se
Corr
FET(R FET(L)
)/RRI
/RRI
A
3min
198
194
0.979798 0.802293 0.440273 0.443683
B
3min
332
322
0.96988 0.911003 0.467319 0.451698
C
3min
225
223
0.991111 0.843615 0.424077 0.411738
D
3min
263
258
0.980989 0.814634 0.482105 0.460597
E
3min
252
249
0.988095 0.863384 0.437047 0.456417
4. Results and Discussion
• Experiments(estimation blood pressure)
–
–
–
–
–
System Initialization
Cuff pressure measuring
Contact system and finomerter simultaneous measurement
Cuff pressure measuring
Over
System
Initial Cuff 量測 Rest
5min
2min
取標準差
取平均值
系統量測/動態式
血壓儀器量測
3min
T:17min
Rest
Cuff 量測 Over
2min
5min
t
4. Results and Discussion
• Experiments(estimation blood pressure)
– Finometer is a noninvasive hemodynamic
cardiovascular monitor based on the measurement
of finger arterial pressure
4. Results and Discussion
• Experiments(estimation blood pressure)
– The actual figure
Cuff pressure
Contact system
Finometer
4. Results and Discussion
• Experiments(estimation blood pressure)
– Blue: Finometer pressure signal
– Black: ECG Signal
– Red: PPG Signal
– Green: Right leg femoral artery pressure
– Yellow: Left femoral artery pressure
4. Results and Discussion
• Experiments(estimation blood pressure)
– Single- and multiple-regression analysis
– BP=a+b*PAT+c*HR+d*TDB+e*FAP
4. Results and Discussion
4. Results and Discussion
• Experiments(estimation blood pressure)
– Performance of cuffless BP estimation with regard
to combinations of parameters used in regression
analysis
Variable
PAT
PAT+HR
PAT+TDB
PAT+FET
PAT+HR+TDB
PAT+HR+FET
PAT+HR+TDB+FET
R
0.93544
0.93619
0.93717
0.93687
0.93796
0.93756
0.93951
SBP
R^2
0.87537
0.87678
0.87857
0.87803
0.88005
0.87932
0.88292
Adj.R^2
0.87478
0.87561
0.87741
0.87686
0.87832
0.87758
0.88066
R
0.59539
0.75456
0.62561
0.60788
0.77345
0.76168
0.77999
DBP
R^2
0.37019
0.57162
0.40257
0.38567
0.60076
0.58208
0.61077
Adj.R^2
0.36708
0.56751
0.39664
0.37956
0.59499
0.57602
0.6032
4. Results and Discussion
• Experiments(estimation blood pressure)
– SBP Scatter plot
5mmHg
5mmHg
4. Results and Discussion
• Experiments(estimation blood pressure)
– DBP Scatter plot
5mmHg
5mmHg
4. Results and Discussion
• Experiments(estimation blood pressure)
– Boxplots
4. Results and Discussion
• Experiments(estimation blood pressure)
– Reproducibility of multiple regression analysis for
BP estimation
SBP  526.465  (1.3813 * PAT )  (0.0012 * HR )  (0.0158 * TDB )  (0.0241* FET )
DBP  265.741  (0.5681* PAT )  (0.0299 * HR )  (0.0358 * TDB )  (0.00267 * FET )
1
0.922729043
0.9
0.8
0.847635012
0.746011445
0.680468163
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
SBP(Training) DBP(Training)
SBP(Test)
DBP(Test)
4. Results and Discussion
• Experiments(estimation blood pressure)
– Reproducibility of multiple regression analysis for
BP estimation
System
Initial Cuff 量測 Rest
5min
2min
取標準差
取平均值
系統量測/動態式
血壓儀器量測
3min
T:17min
Rest
Cuff 量測 Over
2min
5min
t
0.804
0.795
0.710
4. Results and Discussion
• Experiments(estimation blood pressure)
Training
– Reproducibility of multiple regression analysis for
BP estimation
Test
SBP
DBP
1
0.9
0.8
0.944
0.795
0.804
0.710
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
Training
Test
SBP
DBP
4. Conclusions and Future Work
• Conclusions
– 3M Filter remove baseline drift better than IIR
filter
– FET high correlation between the legs average of
0.844
– Multiple regression analysis for SBP and DBP
estimation ,r and r^2 of SBP was 0.939 0.882,r and
r^2 of DBP was 0.779 0.610
– The estimated BP was compared with the
measured BP simultaneously ,the performance
results of this test set decrease a little
4. Conclusions and Future Work
• Future work
– PPG to be more stable
– Build different filters in MCU
– Analyze more subjects
– FET possibility to replace the TDB parameters
– Unconstrained system for BP estimation and
application to home care system or firmware
development
References
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Thank you for your
attention