Proceedings Article | 25 May 2022
KEYWORDS: Heart, Video, Cell phones, Signal processing, Video processing, Linear filtering, Facial recognition systems, Cameras, Signal detection, Photoplethysmography
The prevalence of cardiovascular diseases in China is still on the rise, and it is estimated that 330 million people are suffering from cardiovascular diseases. In terms of physical health and mental health, a heart rate detection technology that is portable can be measured at any time, safe, comfortable, simple to operate, and low-cost is essential. Given the inevitable jitter of handheld mobile phones, based on the accuracy of remote photoplethysmography (rPPG) detection
technology, we propose a moving window timing sampling to refine the original video frame signal. The heart rate value can be extracted by processing such as region of interest (ROI) selection, high-pass filtering, blind source separation algorithm, Fourier transforms, and peak detection. Compared with the heart rate value obtained without using the moving window timing sampling, we found that the effect of the moving window timing is about 10 seconds is the best. The root means as the square error (RMSE), mean absolute error (MAE), and standard deviation (STD) are the lowest, 6.6929, 5.1365, 6.6165 respectively. The errors compared to the sampling without moving piecewise function are 13.53, 10.79, 14.09, The errors were reduced by 50.5%, 52.4%, and 53.04% respectively.
