Development of Piezo-electric Sensor Based Non-invasive Low Cost Arterial Pulse Analyzer

Pradip Gatkine1, Dr. Swati Gatkine2, Sushanth Poojary3, Saket Chaudhary3, Dr. Santosh Noronha3 1. Dept. of Mechanical Engineering, IIT Bombay, Powai Mumbai, India

2. Dept. of Occupational Therapy, Seth G. S. Medical College & K.E.M. Hospital Mumbai, India 3. Dept. of Chemical Engineering, IIT Bombay, Powai Mumbai, India

Email: pradip_gatkine@iitb.ac.in

Abstract: Recent researches have demonstrated implications of Arterial Pulse analysis from Radial and Brachial artery on cardiovascular, renal and autonomic nervous system, as early indicator of major ailments. We have developed a low-cost Arterial Pulse Analyzer which provides run-time display of Arterial Pulse waveforms during the test as well as provides analysis of the waveforms in digitally storable format. The dynamic pressure waves at radial and brachial arteries are recorded non-invasively using piezoelectric ceramic plate sensors. The parameters analyzed are: S-P-T-C-D points, Augmentation index, pulse wave velocity, 2nd derivative analysis for arterial ageing index, Pulse rate variability and Power Spectrum of Pulse rate variability. The setup is portable and consists of 2 straps, one each for Radial and Brachial artery, with sensors mounted on them. Signal Processing and Analysis is done using Python on a Tablet PC. It is aimed to become a potential automatic cardiovascular screening device for public health centers in developing countries as they typically lack medical expertise and access to diagnostic devices for cardiovascular diseases.

Commercially available arterial pulse analyzers are not portable and have an average cost of around 4000USD. This system is portable, requires minimal power and cost 100USD, several of the technologies employed being free or open-source.

Keywords— Arterial Pulse, Piezoelectric Sensor, Radial, Brachial, Cardiovascular, Python.

I. INTRODUCTION Cardiovascular Diseases (CVDs) have recently been

identified as a major cause of mortality across the world. The World Health Report 2004, by World Health Organization (WHO) asserts that 30% of the deaths are attributable to CVDs globally [1]. This is very comparable to the mortality due to communicable diseases.

The shape of the arterial pulse wave is a superimposition of the forward traveling pressure wave with the wave reflected from arterial branches. The amplitude of reflected wave depends on arterial wall stiffness [2]. Changes in the arterial pulse waveform are caused due to several physiological and clinical factors such as ageing, hypertension and diabetes [3,4]. Arteriosclerosis and chronic renal failure can also be predicted at early stages by observing pulse parameters like Peripheral Augmentation Index (AiX) and Time to reflection (TR) [5,6]. Parameters like Pulse Wave Velocity (PWV), Pulse Rate

Variability (PRV) and its Power Spectrum [7] are important pointers to cardiovascular health state. Thus, analysis of the arterial pulse provides a handle on early prediction of CVDs.

Many non-invasive methods have been developed for capturing arterial pulse signals; these include: Arterial Tonometry, Photoplethysmography and Doppler Ultrasound. Arterial Tonometry is most reliable for pulse shape [8]. The commercial Arterial Pulse Analyzer called ‘SphygmoCor’ uses Arterial Tonometry. It synthesizes aortic pulse waveform in addition to above parameters. Commercial instruments giving similar analysis cost around €5000 while some others based on photoplethysmography giving similar parameters of analysis without aortic waveform synthesis cost around 4000USD.

The proposed Arterial Pulse Analyzer (APA) uses Arterial tonometry in which the transducer is placed over the artery position and is depressed a little to obtain clear pulse pressure waveforms without occluding the blood flow. We use a piezoelectric ceramic plate sensor for converting the dynamic pulse pressure waveform into an analog signal. Signals are sampled at 200Hz and are conditioned for noise removal and baseline drift. A python script is written for runtime display of signal and parameter detection. Analyzed parameters are S-P-T-C-D points (Fig. 5) in the wave, AiX, PRV and power Spectrum of PRV of the radial artery pulse wave. Pulse wave velocity is determined using simultaneous measurement of the radial and brachial arterial wave. The device cost is less than 100USD.

The paper outline is as follows. Section II describes System Overview. Algorithms to extract parameters are discussed in Section III. Test results are elaborated in Section IV and conclusions in Section V.

II. SYSTEM OVERVIEW

A. The Transducer The Piezoelectric ceramic plate sensor used here is

manufactured by Murata Manufacturing Co. Ltd. It is a Piezoelectric Diaphragm as shown in Fig.1a and its block diagram in Fig. 1b. This is a family of low cost pressure transducers. These are active transducers and hence the sensitivity and linearity are not affected by input voltage fluctuations.

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Fig. 1a.Piezoelectric Sensor used Fig. 1b. Piezoelectric

When this diaphragm is subjected to a strproduces a polarization P across the electrwhich is given by:

P = d × T, where d is piezoelectric strain co

d 7.41 × 109 V/m for this sensor

This relation is frequency independent fThe arterial pulse is a low frequency signcontaining frequencies less than 10Hz. pressure and strain are linearly related. Thibetween voltage generated and pressure cdynamic sensor and can detect only dynampressure. Hence only shape of pulse pressextracted and not the absolute pressure matransducers of various diameters as well as transducers were tested which lead to particular size on the basis of sensitivity and r

B. Data Acquisition

The data acquisition circuitry comprisevariable amplifier, ADC and microcontrollethat even with the strongest beating pulse swing does not exceed 0.5V. Also it wbaseline drift is of the order of 1V peak to pOperational Amplifier (LM 324) based lewith non-inverting amplifier circuit was utshift the baseline to 3.3V (shift is dependentand to adjust the gain between 1/3 to 2. Tused to ensure optimum use of ADC resoluti

Fig.2 Schematic of Data Acquisition Circuitry. R1=R4from 100K to 220K. Gain = (R4/R1) × (R1+R2)/(R3+R4

C. Low pass Filtering No electronic low pass filter has been appvery difficult to exactly characterize its phasethus the time-domain distortion is caused. Helinear low pass 10th order Butterworth filter w

c sensor block diagram

ain change by T, it rode and the plate

onstant

from 0-50 Hz [9]. nal predominantly For low strains, s ensures linearity change. This is a mic component of sure wave can be agnitudes. Similar piezoelectric film selection of this reproducibility.

s of level shifter, r. It was observed the peak to peak

was observed that eak. Therefore, an

evel-shifter circuit tilized to coarsely t on selected gain)

The level shifter is on.

4=R3=100K, R2 varies 4)

plied, because it is e response and ence, a software

with cut-off

frequency 10 Hz that achieves zby applying an IIR filter to a sigonce backwards. Thus phase-di50Hz AC mains noise is also el

D. Baseline Drift CancellationThe baseline of the

data acquisition and its breasons may include hysterbreathing. Its removal is nwavelet based algorithmdecomposed using ‘sym8’with the pulse signal. It is oat 10th level of decompositbaseline of the signal. It signal for baseline remocorrection are shown in Fig

Fig.3. Pulse Signal befo

E. Operational Details A Velcro based strap h

mount the sensor and ensurewave from pulse position to is used to apply enough presThis strap is usable at both Rpositions. The subject is madrelax for 5 minutes before thpressure point is located by pmarked position of the sensocoincide with the pulse locatto fix the positioning of the ssignal. Then the strap is tighclear waveform without occlReadings are taken for 3 minmeasured using a digital sphafter the pulse measurement

Fig.4. The picture of the setup strap

zero phase delay was designed gnal twice, once forwards and istortions are eliminated. The liminated.

n sensor changes slowly during

behavior is unpredictable. The resis or motion artifacts due to

necessary and is achieved using m. The signal was wavelet ’ wavelet due to its similarity observed that the approximation tion matches very closely to the is appropriately removed from

oval. The results of baseline g. 3.

fore and after baseline correction

has been designed to flexibly e substantial transfer of pressure the sensor. An adjustable strap

ssure by appropriate tightening. Radial and Brachial artery de to lie in supine position and he readings are taken. The pulse palpation and is marked. The or on the strap is then made to tion. A runtime display is used strap where we obtain the best

htened a little so that we get a lusion of arterial blood flow. nutes. Blood pressure is hygmomanometer (Omron Co.)

is completed.

with tablet and radial artery

Fig.5. Characteristic SPTCD points (Source: DANTpoints as identified by the program (marked as dots).

III. PARAMETER EXTRACTI

After the data acquisition is initialized, tfor 5 seconds to stabilize the system. The within 5 seconds after data acquisition is c(Aakash Tablet) running Linux (Ubuntu 1processing and display unit to make the entirand low cost. All parameter extraction algoritbelow:

A. S-P-T-C-D Points A representative arterial pulse signal is

with S-P-T-C-D points depicted. These pointpeak detection algorithm. It is inspired frderivative of the signal is calculated and th(M) is recorded in a data window of 5 secondderivative (simple local maxima detection) ttimes the maximum value are noted (Mi). each such point the immediate next and impoints of zero derivative are noted which aresystolic and diastolic points (Pss, Psd).difference between systolic and diastolic difference is within 50% of the differencemaximum 1st derivative point (M), then thqualified as real systolic and diastolic poinshowed remarkable accuracy of 90% on an av

After S and P points, the algorithm for Tbelow:

Fig.6 Partial Flowchart of T-C-D point detection

Start point P(i)

Find immediate next maxima of 1

st

derivative

Find immediate next minima of 1

st

derivative

Find immediate next maximum of

1st derivative

Find immediate next minimum of 1

st

derivative

S(i+1) reached?

END

TEST) and S-P-T-C-D

ION the program waits data is processed

complete. A tablet 12.04) is used as re system portable thms are described

s shown in Fig. 4 ts are extracted by

rom [8]. The first he maximum value ds. The peaks in 1st that are above 0.5 Corresponding to

mmediate previous e treated as pseudo The magnitude are noted. If the corresponding to

he Pss and Psd are nts. This algorithm verage.

T-C-D is described

Next, the program searches these 4 critical points. They arand D points. If there are no zethe two consecutive critical poin

B. 2nd Derivative Analysis: The A-B-C-D-E points (Fig

important in determining artracking from 5 samples befoclose to S(i) ) and search for well as 1st and 2nd minima qualify respectively as A, C, E,

Fig.7 2nd Derivative with A-B-Cprogram) and the corresponding Pu

C. Peripheral Augmentation InThis is the Augmentation

arteries such as Radial artery. It

pAix = (Pressure at T

=

The blood pressure measurto the program to find out pAiX

D. Pulse Rate and Pulse Rate Interpulse interval is deter

the time of S points of conseper unit time) at every pulse iand is plotted as a function known as Pulse rate variasmoothened with cubic spline curve is used for finding the pouseful to determine autonomic

(a) Fig.8a. Pulse Rate Variability (ingreen cross) ; Fig.8b. Power Spec

for a zero derivative in between re respectively qualified as T, C eros in between, then average of nts is qualified as T, C or D.

g. 8) on 2nd derivative curve are rterial ageing [10]. We start ore S(i) (since 1st maxima lies 1st, 2nd and 3rd local maxima as on 2nd derivative curve. They , B and D.

C-D-E points (identified as dots by the ulse signal

ndex (pAiX) index evaluated at peripheral

t is defined as [10]:

T) / (Pressure at P) × 100

× 100

red at brachial artery is supplied X.

Variability (PRV) rmined by taking differences in cutive waves. Pulse rate (beats is evaluated using this quantity of beat number. This curve is

ability. The curve is further interpolation. The smoothened

ower spectrum(Fig. 8b) which is nervous system health state [7].

(b) n blue line) with interpolated curve (in ctrum of PRV

E. Pulse Wave Velocity (PWV) We measure Brachial-Radial pulse

(BRPWV) using this setup. One strap is appamplitude position of Radial artery and othamplitude position of brachial artery. Thsupine position. The distance between themeasured. After simultaneous acquisition othe straps, the time difference between corrP position is measured and pulse wave veloby taking the mean time-delay.

Fig.9. Brachial Artery Signals (in blue) and Radgreen) with their P points identified

IV. TEST RESULTS The setup has been tested on several

males, females and diversity of age from 2compared the credibility of the method parameters: Pulse rate, pAiX and PWV. For healthy male individuals in age group 20-30 y

A. Pulse Rate: The subjects were asked to relax in the wa

previously and their pulse was palpated by a tfor 1 minute and the pulse rate was measuredrepeated 3 times with relax interval of 1 minuwas taken. The average pulse rate obtained byminutes is compared.

Fig.10. Pulse Rate (beats per minute) as measured byas measured by device (Red).

Fig.11. Augmentation Index (in %) as measured by the d

wave velocity plied at the strong her strap at strong he subject lies in se two sensors is

of signals by both responding pulses’ ocity is calculated

dial Artery Signals (in

subjects including 20 to 60. We have

based on three this, we selected 5 years.

ay described trained physician

d. This was ute and average y the APA after 3

y Physician (Blue) and

device for 5 subjects

Fig.12. PWV as measured by the d

B. Augmentation Index: Peripheral Augmentation i

for all the individuals using Aagainst the standard range of vmales in age-group 20-30 years

C. Pulse Wave Velocity (PWV)The PWV(Brachial-Radial)

individual with APA device anstandard range for both males the values are almost within the

CONCL

From the above testing it device is a potential low cost alow cost screening setups indispensable. Further developautomated diagnostic device wthank Aakash Tablet team for t

REFER

[1] World Health Organization (200sex and mortality stratum in WHThe world health report 2004 - ch

[2] Meyer, B.J. Meij, H.S. Meyer, AJuta & Co, Ltd, 1997.

[3] Benetos A, Waeber B, Izzo JSafar M. Influence of age, renal disease on arterial Hypertens 2002; 15: 1101-8.

[4] Cruickshank, K., Rista, L., AnGosling, R.G., “Aortic pulse-wmortality118 in diabetes and glocno. 16, p. 2085, 2002.

[5] O’Rourke, M.F., Pauca, A., Jiangmethods in human cardiovascula2001.

[6] Savage, M.T., Ferro, C.J.,“Reproducibility of derived centchronic renal failure,” Clinical Sc

[7] Aniruddha J. Joshi et.al., “Artediagnoses”, IEEE, 2008.

[8] Salter, G. D., “Design and validdevice”, unpublished.

[9] http://www.symmetron.ru/supplie[10] D. Korpas et.al., “Parameters de

58: 473-479, 2009 [11] Farro I. et.al. “Pulse Wave Velo

disease”, International Journal of[12] Chung J. W . et.al., “Reference

pulse pressure in apparently hJ. 2010 April; 40(4): 165–171.

device in m/s for 5 subjects.

ndices were measured (Fig.11) APA device and were compared values for healthy individuals for s. (within 81.2 ± 12.9 % ).[12]

V): ) was measured(Fig.12) for each nd they were compared with the and females. It is found that all e range (8.8 ± 1.5m/s). [11]

LUSION is clear that the proposed APA

alternative which can be used in where a portable device is

pments can be done towards an with several clinical trials. We their kind support.

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