Using the Characteristics of Pulse Waveform to Enhance the Accuracy of Blood Pressure Measurement by a Multi-Dimension Regression Model
Department of Computer Science and Information Engineering, Chaoyang University of Technology, Taichung 41349, Taiwan
Department of Electrical Engineering, National Taiwan University, Taipei 10672, Taiwan
Division of Cardiology, Chiayi Chang Gung Memorial Hospital, Chiayi 61363, Taiwan
Department of Traditional Chinese Medicine, College of Medicine, Chang Gung University, Taoyuan 33305, Taiwan
Biomedical Information Engineering Laboratory, The University of Aizu, Aizu-wakamatsu 965-8580, Fukushima, Japan
Department of Electrical Engineering, National Taipei University of Technology, Taipei City 10608, Taiwan
Author to whom correspondence should be addressed.
Appl. Sci. 2019, 9(14), 2922; https://doi.org/10.3390/app9142922
Received: 17 June 2019 / Revised: 12 July 2019 / Accepted: 18 July 2019 / Published: 22 July 2019
With the advancement of wearable technology, many physiological monitoring instruments are gradually being converted into wearable devices. However, as a consumer product, the blood pressure monitor is still a cuff-type device, which does perform a beat-by-beat continuous blood pressure measurement. Consequently, the cuffless blood pressure measurement device was developed and it is based on the pulse transit time (PTT), although its accuracy remains inadequate. According to the cardiac hemodynamic theorem, blood pressure relates to the arterial characteristics and the contours of the pulse wave include some characteristics of the artery. Therefore, the purpose of this study was to use the contour characteristics of the pulses measured by photoplethysmography (PPG) to estimate the blood pressure using a linear multi-dimension regression model. Ten subjects participated in the experiment, and the blood pressure levels of the subjects were elevated by exercise. The results showed that the mean and standard deviation (mean ± SD) of the root mean square error of the estimated systolic and diastolic pressures within the best five parameters were 6.9 ± 2.81 mmHg and 4.0 ± 0.65 mmHg, respectively. Compared to the results that used one parameter, the PTT, for estimating the systolic and diastolic pressures, 8.2 ± 2.1 mmHg and 4.5 ± 0.79 mmHg, respectively, our results were better.