Non-contact continuous blood pressure monitoring from video

This paper presents a non-contact continuous blood pressure detection method based on video. This method integrates the correlation between systolic blood pressure and diastolic blood pressure, and realizes non-contact continuous blood pressure monitoring of individuals. In this method, finger videos are collected by ordinary industrial cameras, and imaging photoplethysmography (IPPG) signals are extracted. De-trending and band-pass filtering are used to remove the baseline drift and noise of original IPPG signal. And an effective single IPPG signal is screened by limiting the number of sampling points, the amplitude changes of the starting point and the ending point and whether there is a dicrotic wave, and the characteristics of signal such as peak value, systolic time, diastolic time and pulse width are extracted, and the regression models of systolic blood pressure and diastolic blood pressure are established respectively, finally the noncontact detection of individual blood pressure is realized. The experimental results show that this method has high accuracy, the mean absolute error (MAE) of systolic blood pressure is 1.34 mmHg, the mean error (ME) is 0.46 mmHg, the standard deviation (STD) is 1.95 mmHg; the mean error (MAE) of diastolic blood pressure is 1.59 mmHg, the mean error (ME) is 0.36 mmHg, and the standard deviation (STD) is 2.01 mmHg.