Towards wearable blood pressure measurement systems from biosignals: a review

Authors: ÜMİT ŞENTÜRK, KEMAL POLAT, İBRAHİM YÜCEDAĞ

Abstract: Blood pressure is the pressure by the blood to the vein wall. High blood pressure, which is called silent death, is the cause of nearly 13 % of mortality all over the world. Blood pressure is not only measured in the medical environment, but the blood pressure measurement is also a need for people in their daily life. Blood pressure estimation systems with low error rates have been developed besides the new technologies and algorithms. Blood pressure measurements are differentiated as invasive blood pressure (IBP) measurement and noninvasive blood pressure (NIBP) measurement methods. Although IBP measurement provides the most accurate results, it cannot be used in daily life because it can only be performed by qualified medical staff with specialized medical equipment. NIBP measurement is based on measuring physiological signals taken from the body and producing results with decision mechanisms. Oscillometric, pulse transit time (PTT), pulse wave velocity, and feature extraction methods are mentioned in the literature as NIBP. In the oscillometric method of the sphygmomanometer, an electrocardiogram is used in PTT methods as a result of the comparison of signals such as electrocardiography, photoplethysmography, ballistocardiography, and seismocardiography. The increase in the human population and worldwide deaths due to the highly elevated blood pressure makes the need for precise measurements and technological devices more clear. Today, wearable technologies and sensors have been frequently used in the health sector. In this review article, the invasive and noninvasive blood pressure methods, including various biosignals, have been investigated and then compared with each other concerning the measurement of comfort and robust estimation.

Keywords: Electrocardiography, photoplethysmography, biosignals, cuffless blood pressure estimation, wearable measurement systems, machine learning

Full Text: PDF