Non-contact continuous blood pressure measurement based on imaging equipment

An optical and non-contact continuous measurement method to detect human blood pressure through a high-speed camera is discussed in this paper. With stable ambient light, photoplethysmographic (PPG) signals of face and palm area are obtained simultaneously from the video captured by high-speed camera, whose frame rate should be higher than 100 frames per second. Pulse transit time (PTT) is measured from the R-wave distance between the two PPG signals. The Partial least squares regression( PLSR) model was established to train the samples, and the relationship between PTT and blood pressure, including intra-arterial systolic pressure (SBP) and diastolic pressure (DBP), was established to obtain blood pressure. Compared with the output of traditional sphygmomanometer, the blood pressure data collected from non-contact system has little error and meets the fitting conditions. We first proposed an accurate video-based method for non-contact blood pressure measurement using machine learning, and the average error of SBP is 0.148mmHg and of DBP is 0.359mmHg.