Remote Photoplethysmography Heart Rate Variability Detection Using Signal to Noise Ratio Bandpass Filtering

Abstract

Heart rate variability (HRV) is a measurement for cardiovascular health condition, and it can be obtained from photo-plethysmography signal by capturing the slight color change in human skin as a result of blood volume change. Remote photoplethysmography signals (rPPG) can be extracted from videos of human faces. Current rPPG signal postprocessing typicall y selects a certain fixed range of the frequency in the power spectrum of the signal. This paper describes a method to use signal to noise ratio to assist in the selection the adaptive range of the frequency that may contain HRV information. UBFC-rPPG dataset is used for validation. The experiment result shows a regression result of 0.88 correlation in the results from the face video compared to the ground truth data in SDRR and 0.63 in RMSSD. The proposed method of this paper has a better accuracy compared to the classical methods, to the best of our knowledge.