A Novel Contactless Blood Pressure Measurement System and Algorithm Based on Vision Intelligence

Abstract

The measurement of vital signs such as blood pressure plays a key role in human health. Usually, we encounter some problems when we check them in the traditional way; for example, it is impossible to check continuously, and measuring vital signs requires direct contact with the patient, which can be uncomfortable for certain individuals. In this research, we present a vision-based system for estimating blood pressure using pulse transit time (PTT) and the Eulerian video magnification (EVM) technique to amplify tiny color variations caused by blood flow to calculate arterial pulse waves traveling between two arterial sites. Calculating the PTT by processing the video signal for each subject, an oscillometer BP device was used to evaluate the performance between measurements in different conditions, including rest, exercise, and during recovery. Mean systolic BP was 115 mmHg at rest, 137 mmHg during high-intensity exercise, and 114 mmHg during recovery, respectively. The average value of diastolic blood pressure did not change significantly before, during, and after exercise. When we compared the systolic and diastolic blood pressure with ground-truth results, our system showed an accuracy of 91% for systolic blood pressure and 90% for diastolic blood pressure.