Contactless Blood Pressure Estimation System Using a Computer Vision System

Abstract

Blood pressure (BP) is one of the most common vital signs related to cardiovascular diseases. BP is traditionally measured by mercury, aneroid, or digital sphygmomanometers; however, these approaches are restrictive, inconvenient, and need a pressure cuff to be attached directly to the patient. Therefore, it is clinically important to develop an innovative system that can accurately measure BP without the need for any direct physical contact with the people. This work aims to create a new computer vision system that remotely measures BP using a digital camera without a pressure cuff. The proposed BP system extracts the optical properties of photoplethysmographic signals in two regions in the forehead captured by a digital camera and calculates BP based on specific formulas. The experiments were performed on 25 human participants with different skin tones and repeated at different times under ambient light conditions. Compared to the systolic/diastolic BP readings obtained from a commercial digital sphygmomanometer, the proposed BP system achieves an accuracy of 94.6% with a root mean square error (RMSE) of 9.2 mmHg for systolic BP readings and an accuracy of 95.4% with an RMSE of 7.6 mmHg for diastolic BP readings. Thus, the proposed BP system has the potential of being a promising tool in the upcoming generation of BP monitoring systems.