Research On Non-contact Heart Rate And Blood Pressure Estimation Based On Pixel Selection

Heart rate and blood pressure are important physiological parameters that characterize an individual’s health status.Imaging photoplethysmography is a method of capturing skin color changes caused by the heart beating cycle through a camera.The pulse signal obtained by this method can be used for the estimation of heart rate and blood pressure.This paper will complete the estimation of heart rate and blood pressure based on imaging photoplethymography.The main tasks are as follows:(1)The key to non-contact heart rate and blood pressutre estimation is to extract high-quality pulse signals.In this paper,an adaptive skin pixel selection algorithm(SA-HSV)is proposed to process the video frame images of the extracted pulse signal and improve the misjudgment existing in the traditional skin pixel selection algorithm.phenomenon,improve the recognition accuracy.The algorithm is applied to the VIPL-HR public data set and the self-collected data set,and a range of experimental scenarios are set up to evaluate and analyze SA-HSV performance.The average absolute error of heart rate estimation obtained from self-collected data is 3.56bpm.(2)By extracting the features related to blood pressure in the pulse signal,a blood pressure estimation model based on the features of the pulse signal is established.The self-collected data sets were used to build radial basis neural network and BP neural network respectively to verify the blood pressure estimation.The estimation error of the simulated BP is lower than radial basis neural network.The particle swarm method has a better optimization effect,with a systolic blood pressure estimate error of 0.13±7.91mmHg and a diastolic blood pressure estimation error of-0.12 ±6.40mmHg.The estimated error matched the blood pressure measurement standards of AAMl and BHS.Within a specific estimation error range,the estimated accuracy of systolic blood pressure was 92.39%,the estimated accuracy of diastolic blood pressure was 98.36%.The experimental results validate the efficacy of the adaptive pixel selection technique when used to estimate non-contact heart rate and blood pressure.The method proposed in this paper provides a reference for practical applications in the field of non-contact physiological parameter estimation.