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Noninvasive Cuffless Estimation of Blood Pressure using Photoplethysmography without

Electrocardiograph Measurement Rohan Samria1, Ridhi Jain2, Ankita Jha3, Sandeep Saini4, Shubhajit Roy Chowdhury5,

1, 2, 3, 4 Department of Electronics and Communication Engineering, The L.N.M Institute of Information Technology Jaipur, India

5 Centre of VLSI Design and Embedded Systems, IIIT Hyderabad, India

Abstract The paper presents a novel approach of measuring blood pressure using Photoplethysmography (PPG). It is a non-invasive, cuffless and painless technique that deploys infrared light to detect small variation in blood volume in the tissues with each cardiac cycle. Few specific features (viz. systolic upstroke time (ST), diastolic time (DT) and the time delay between the systolic and diastolic peak (T1)) of the waveform obtained via this technique were examined and correlated with the arterial blood pressure in 22 subjects of two age groups i) 18-25 years ii) 26-50 years. It was observed that there is a good correlation of blood pressure (both systolic blood pressure (SBP) and diastolic blood pressure (DBP)) with diastolic time and also with the time delay between systolic and diastolic peak.

Keywords blood pressure, photoplethysmography, systolic blood pressure, diastolic blood pressure, systolic upstroke time, diastolic time.

I. INTRODUCTION Heart diseases have become a major reason for high mortality therefore a non-invasive and continuous system for monitoring cardiovascular parameters would be of great interest to doctors [1]. One of the most important parameters for the assessment of cardiovascular system is blood pressure. High blood pressure may lead to cardiovascular diseases and consequently is a risk factor for death.

Blood pressure (BP) is the pressure exerted by circulating blood upon the walls of blood vessels. During each heartbeat, blood pressure varies between a maximum (systolic) and a minimum (diastolic) pressure.

Currently, the most common device used for blood pressure measurement is a sphygmomanometer, composed of an inflatable cuff to restrict blood flow and a mercury or mechanical manometer to measure the pressure [2]. Such devices can be used for measurement at regular intervals. However, since the cuff needs inflation and deflation, it cannot provide beat-to-beat measurement of blood pressure. A continuous measurement might provide more useful information about a persons health. Also, a cuffless design will be painless and more convenient to use.

Photoplethysmography (PPG) is one such technique, which can be used to predict many vital health concerned parameters such as blood pressure, heart rate, hemoglobin and blood glucose level [3]. It is reported that noninvasive, cuffless and

continuous measurement of BP can be done using this technique [3] [4]. It uses an Infrared Light Emitting Diode (IR LED) and a corresponding photodiode to measure small blood volume changes in the arteries. The PPG waveform has an AC and a DC component. The AC component is attributed to the cardiac synchronous changes in the blood volume with each heartbeat whereas the DC component relates to the tissues and to the average blood volume [3].

In recent decades, many research efforts have been expended in the field of non-invasive, continuous BP estimation by cardiovascular surrogate parameters, mainly the pulse transit time (PTT) [5] [6]. However, the BP predictions based on PTT requires PPG with an additional measurement of electrocardiogram (ECG) which requires the attachment of electrodes on the surface of human body. In order to accomplish a completely non-constrained measurement, we investigated a method of predicting BP without ECG from only one channel PPG waveform

II. CIRCUIT DESCRIPTION The block diagram of the

circuit is illustrated in Fig. 1. The output of the circuit was further observed on Digital Signal Oscilloscope (DSO) for analysis and blood pressure estimation.

The finger is illuminated with IR LED and the transmitted light is detected using photodiode. The photodiode generates a current which is proportional to the intensity of light falling on it. This photo generated current is converted to voltage using a transimpedance amplifier. The signal obtained needs conditioning as it has very small amplitude and is also infested with a huge amount of noise. This signal is thus amplified using an inverting amplifier. To filter out the noise, passive high pass filter of cutoff frequency 0.6 Hz and active low pass filter of cutoff frequency 8 Hz have been used [7].

Fig. 1 Circuit flowchart

PASSIVE HIGH

PASS FILTER INFRARED

LED

PHOTODETECTOR & TRANSIMPEDANCE

AMPLIFIER

TO DIGITAL

SIGNAL

ACTIVE LOW PASS

FILTER

AMPLIFIER

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TABLE I. CORRELATION COEFFICIENT OF ST, DT AND T1 WITH BLOOD PRESSURE

III. METHODOLOGY

The waveform obtained from the PPG circuit and the blood pressure values given by OMRON digital BP monitoring machine were simultaneously recorded several times for 22 subjects of two different age groups, one from 18-25 years and the other from 26-50 years. The recorded readings of BP and the important parameters of PPG wave (systolic upstroke time (ST), diastolic time (DT) and the time delay between the systolic and diastolic peak (T1)) were averaged for all the subjects. Thereafter, the systolic blood pressure (SBP) and diastolic blood pressure (DBP) were estimated by taking the correlation of the recorded SBP and DBP with the parameters of PPG wave and then finding the linear regression with them.

A. Calculation of Systolic-upstroke time (ST), Diastolic time (DT) and the time delay (T1)

In order to find optimal parameters for estimating blood pressure, three features of PPG signals were analysed as shown in Fig. 2, namely systolic-upstroke time (ST), diastolic time (DT) and the time delay between the systolic and diastolic peaks (T1). While determining the values of these parameters, the accurate position of the crests and troughs are important. In some PPG recordings, it is difficult to find the accurate position of the peaks and the foot because of the poor signal quality. Such signals were dealt with carefully and recorded again.

B. Estimation of the Blood Pressure using Systolic-upstroke time (ST), Diastolic time (DT) and the time delay (T1)

Correlation of actual BP values is found with ST, DT and T1 which is an estimate of how well these parameters fit with it [8]. These time parameters decrease as the BP increases and vice versa therefore we get a negative correlation coefficient of SBP and DBP with each of these parameters. A linear regression equation is then found by taking these parameters as input to estimate the SBP and DBP [9].

The novel approach of this paper is that ECG has not been used and the blood pressure is estimated just using PPG waveform. The old techniques which take use of both PPG and ECG relies on the parameter called PTT (pulse transit time) that requires two different channels to measure the time interval, which makes it less convenient. In this study, however, PTT has not been used as a parameter for estimation of blood pressure, rather, the basic parameters of the PPG waveform such as ST, DT and difference between the systolic and diastolic peak (T1) have been used to find the correlation co-efficient (with SBP and DBP) and consequently the regression equations. This approach not only minimises the cost of using ECG but also is more practical as it requires only one channel.

IV. CALCULATIVE METHOD FOR BLOOD PRESSURE ESTIMATION

A. Relation With Blood Pressure The experimental method was accomplished as following

After BP and PPG signals were measured for 22 subjects,

optimal parameters were recorded and averaged over a specific time period. The standard BP measured from subjects indicated that the SBP was in the range of 113-140 mmHg, while the DBP was in the range of 69-97 mmHg in the age group of 25-50 years. On the other hand, in the age group of 18-25 years, the SBP was in the range of 95 -120 mmHg, while the DBP was in the range of 57-70 mmHg. The range of both SBP and DBP are lower in the case of later group due to the stiffness factor. With age the stiffness of arterial walls increases thus in the older age group, the range of blood pressure shifts to higher level.

Correlation between BP and the important parameters of PPG waveform were computed and observed for both the age groups.

i. In the age group of 26-50 years, the correlation between DBP and T1 was highest (correlation coefficient -0.923), followed by the correlation between SBP and the DT (correlation co-efficient -0.869).

ii. In the age group of 18-25 years, the highest correlation was between DBP and DT (correlation co-efficient -0.811), and between DBP and T1 (correlation co-efficient -0.779), but no proper correlation was found for SBP in this age group.

PARAMETERS AGE 18-25 AGE 26-50

SBP DBP SBP DBP

ST -0.495 -0.403 -0.148 -0.417

DT -0.136 -0.811 -0.869 -0.471

T1 0.044 -0.779 -0.664 -0.923

Fig. 2 PPG waveform and its important parameters

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From Table-I, it is clearly seen that the correlation of all these parameters are negative with the BP. Thus, these results are in accordance with the fact that these time parameters are inversely proportional to the blood pressure.

B. Estimating The Formula The distribution of diastolic and the systolic blood pressure in relation to the above parameters (ST, DT, T1) is given by linear regression line derived using LINEST function in Microsoft Excel. This has been illustrated in graphical form in Fig. 3 and Fig. 4. Further, the y-intercept and the slope of linear equations are presented in tabular form with their respective root mean square error (RMSE) in Table-II

i. The SBP and DBP, in the age group of 26-50 years, have almost similar slope of the linear regression line with respect to DT but have remarkable differences in the y-axis intercept. The best linear regression line is obtained between DBP and T1 in this age group.

ii. In the

between DBP and DT. Also in this age group the linear regression of DBP was quite good with T1 but no relation fitted well for SBP due to its poor relation with all the parameters.

ii. In the age group of 18-25 years, the best linear regression was found between DBP and DT. Also in this age group the linear regression of DBP was quite good with T1 but no relation fitted well for SBP due to its poor correlation with all the parameters.

V. CONCLUSION The DBP, in the age group of 18-50 years, estimated

by our linear regression formula by taking diastolic time as the input parameter is close to that predicted by the digital BP monitoring machine, with a RMSE of 2.625mmHg, whereas the DBP estimated by our linear regression formula obtained using T1 as the parameter has a RMSE of 2.817mmHg.

In the 26-50 age groups, the SBP is best correlated with diastolic time, with a RMSE of 3.521mmHg, whereas the DBP is best correlated with the parameter T1 with a RMSE of 3.285mmHg.

Fig. 4 Linear regression graphs between various parameters (Age group: 18-25 years)

Fig. 3 Linear regression graphs between various parameters (Age group: 26-50 years)

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The parameter T1 which is the time delay between systolic and diastolic peak gave good results in estimation of DBP in both the age groups, we suggest that it can replace DT for more accurate estimation.

Our method of investigation in this paper requires only analysis of PPG waveform for BP estimation and not the ECG signal. Even though the method is not highly accurate, it is non-invasive, cuffless and painless which can predict the BP on a beat-to-beat basis. This work could be made more useful by automating the whole procedure using a microcontroller and improving the accuracy by choosing more sensitive components for filtering.

VI. REFERENCES [1] Zbignevs Marcinkevics, Mara Greve, Juris Imants Aivars, Renars

Erts, Aram Hussain Zehtabi, Relationship between arterial pressure and pulse wave velocity using photoplethysmography /during the post-exercise recovery period. Acta Univesitatis Latviensis: Biology, 753, 59-68.

[2] Cheah Kim Wei, Photoplethysmography Blood pressure measurement.

[3] John Allen, Photoplethysmography and its application in clinical physiological measurements. Physiol. Meas.28, R1-R39 (2007)

[4] X. F. Teng and Y. T. Zhang, Continuous and noninvasive estimation of arterial blood pressure using a photoplethysmographic approach, 25th Annual International Conference of the IEEE Medicine and Biology Society, 2003.

[5] Soo-young Ye, Gi-Ryon Kim, Dong-keun Jung, Seong-wan Baik and Gye-rok Jeon, Estimation of systolic and diastolic pressure using the Pulse Transit Time. World Academy of Science, Engineering and Technology 67 2010

[6] Revati Shriram, Asmita Wakankar, Nivedita Daimiwal and Dipali Ramdasi, Continuous Cuffless Blood Pressure Monitoring Based on PTT. Department of Instrumentation and Control Cummins College of Engineering for Women, Pune, no. 411052.

[7] Geert Langereis, Photoplethysmography (PPG) system, Version 2, Feb 2010.

[8] Youngzoon Yoon and Gilwon Yoon, Non-constrained Blood pressure measurement by Photoplethysmography, Journal of Optical Society Of Korea, Vol. 10, No. 2, June 2006, pp. 91-95

[9] Qiao Zhang,Cuff-free blood pressure estimation using signal processing techniques, Thesis Submitted to the College of Graduate Studies and Research, Division of Biomedical Engineering University of Saskatchewan Saskatoon, August, 2010.

PARAMETERS AGE 18-25 AGE 26-50

SLOPE Y-INTERCEPT RMS ERROR SLOPE Y-INTERCEPT RMS ERROR SBP ST -0.569 173.962 7.305 - - -

SBP DT - - - -0.095 188.581 3.521

DBP DT -0.028 81.396 2.625 -0.062 119.923 7.608

DBP - T1 -0.120 96.711 2.817 -0.344 174.308 3.285

TABLE II. SLOPE, Y-INTERCEPT AND ROOT MEAN SQUARE ERROR

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