scholarly journals Development of Continuous Blood Pressure Measurement System Using Photoplethysmograph and Pulse Transit Time

2021 ◽  
Vol 3 ◽  
pp. 8-12
Author(s):  
Hong Long Pua ◽  
Kok Beng Gan
Keyword(s):  
Blood Pressure ◽  
Blood Volume ◽  
Transit Time ◽  
Pressure Measurement ◽  
Continuous Measurement ◽  
Blood Pressure Measurement ◽  
Pulse Transit Time ◽  
Volume Changes ◽  
Non Invasive

It is not only a problem for old age anyone. So, blood pressure is the one provides importance information with vital signs about cardiovascular health using oscillometric method. Unfortunately, this method required inflation and following deflation of the cuff. This method only gives instantaneous blood pressure and continuous measurement is not available. It is not available to the patients that required long term monitoring. To overcome this problem, the development of Continuous Non-Invasive Blood Pressure (NIBP) algorithm based on Pulse Transit Time (PTT) using two channel Photoplethysmograph (PPG) is proposed in this study. PPG is a non-invasive device for detecting blood volume changes can be affected by various physiological factors, analysis of the PPG signal can provide sufficient information on the human health condition; more specifically their cardio-vascular related performance. Literatures show that the PTT has linear relationship with blood pressure. Nevertheless, the determination of the model structure, order and real-time implementation to offer a continuous measurement of the PTT still remains challenging tasks in this area. PTT can be as index to monitor cardiovascular disease. In this project, dynamic model based on pulse transit time will be proposed to continuously monitor blood pressure by using PPG signals. Different kind of resolutions in microcontroller combined with PPG sensor will be used as well. MATLAB software is also been applied for PTT calculation based on two PPG sensors. PPG is method for detect blood volume changes with optical source transmitter send from one end and received the signal from another by receiver through body tissue as medium. MATLAB functions as Digital Signal Processing (DSP) for signals received in computer. Linear Regression technique and Fung's algorithm are applied to obtain the best fit line for all the points in order to systolic and diastolic blood pressure measurement. The results showed that the algorithm based on pulse transit time has been developed for the assessment of blood pressure and justify patient’ condition with 86.34% and 88.20% accuracy. Finally, this technique is a simple, user friendly and operator independent PPG system suitable for long term and wearable blood pressure monitor.

scholarly journals Pengukuran Tekanan Darah Non-Invasive Tanpa Manset Menggunakan Metode Pulse Transit Time Berbasis Machine Learning Multivariat Regresi

2019 ◽  
Vol 10 (1) ◽  
pp. 61
Author(s):  
Ernia Susana
Keyword(s):  
Machine Learning ◽  
Blood Pressure ◽  
Transit Time ◽  
Pressure Measurement ◽  
Blood Pressure Measurement ◽  
Sequential Estimation ◽  
Pulse Transit Time ◽  
P Value ◽  
Oscillometric Method ◽  
Non Invasive

<p>Currently used non-invasive blood pressure (NIBP) measurements (oscillometric method) has disadvantages related to pumping cuffs which can cause discomfort for patients due to pressure from pumping cuffs.  The aim of this study was to measure blood pressure in a non-invasive manner without cuffs with the Pulse Transit Time (PTT) methodbase on machine learning technology.The blood pressure measurement by the PTT method is obtained from the calculation of the distance of the R-ECG wave with the peak signal <em>photoplethysmogram</em><em> </em>(PPG). The main problem of the PTT method in some previous studies is that the estimation of systolic (SBP) and diastolic (DBP) values is still inaccurate. The blood pressure measurement method in this study used a combination of PTT calculations with machine learning multivariate regression. Therefore expected to obtain a more accurate estimate of systolic (SBP) and diastolic blood pressure (DBP). This study is a laboratory experiment research on 30 healthy volunteers aged 20 ± 1 years. The measurement of the blood pressure value of the PTT-to-oscillometric method is 5 ± 5 mmHg. The blood pressure values generated by this PTT method have a p-value for the sequential estimation of SBP and DBP of 0.7374 and 0.0262.<strong></strong></p>

scholarly journals PTT-based Contact-less Blood Pressure Measurement using an RGB-Camera

2021 ◽  
Vol 7 (2) ◽  
pp. 375-378
Author(s):  
Carolin Wuerich ◽  
Robin Rademacher ◽  
Christian Wiede ◽  
Anton Grabmaier
Keyword(s):  
Blood Pressure ◽  
Diastolic Blood Pressure ◽  
Pressure Measurement ◽  
Blood Pressure Measurement ◽  
Systolic Pressure ◽  
Pulse Transit Time ◽  
Invasive Blood Pressure ◽  
Non Invasive ◽  
Individual Calibration ◽  
Cardiac System

Abstract Commonly used blood pressure measurement devices have noticeable limitations in accuracy, measuring time, comfort or safety. To overcome these limitations, we developed and tested a surrogate-based, non-invasive blood pressure measurement method using an RGB-camera. Our proposed method employs the relation between the pulse transit time (PTT) and blood pressure. Two remote photoplethysmography (rPPG) signals at different distances from the heart are extracted to calculate the temporal delay of the pulse wave. In order to establish the correlation between the PTT values and the blood pressure, a regression model is trained and evaluated. Tests were performed with five subjects, where each subject was recorded fifteen times for 30 seconds. Since the physiological parameters of the cardiac system are different for each person, an individual calibration is required to obtain the systolic and diastolic blood pressure from the PTT values. The calibration results are limited by the small number of samples and the accuracy of the reference system. However, our results show a strong correlation between the PTT values and the blood pressure and we obtained a mean error of 0.18 +/- 5.50 mmHg for the diastolic blood pressure and 0.01 +/- 7.71 mmHg for the systolic pressure, respectively.

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