关键词: 成像式光电容积描记法, 变分模态分解法, 能量熵, 自适应去噪, 非接触测量, 心率, 呼吸率

Abstract:

Imaging Photoplethysmography（iPPG） is a non-contact physiological parameter detection method using videos, but the performance of this method is easily affected by external conditions, especially sensitive to changes of ambient light and head movements. Therefore, in order to eliminate the influence of noise, this paper proposes a method based on adaptive denoising of related energy entropy threshold of Variational Modal Decomposition（VMD） and Variance Characterization Series（VCS） for obtaining anti-interference and non-contact physiological parameters according to the time-frequency characteristics of noise and iPPG signals. Firstly, Variational Modal Decomposition（VMD） method is used to decompose the iPPG signal obtained from the face video image into a series of Intrinsic Mode Functions（IMF） with certain bandwidth and frequency from high frequency to low frequency, and then the noise energy entropy of each sub-interval of the intrinsic mode functions is calculated respectively to obtain the threshold value of the component. Next, the reconstructed denoising signal is obtained by threshold processing. Finally, Variance Characterization Series（VCS） is used to detect the quality of the reconstructed signal, so as to adaptively select different signal analysis methods and realize accurate estimation of physiological parameters of heart rate and respiration rate. The proposed method is validated by the public dataset and the self-collected dataset. The experimental results demonstrate that the proposed method has stronger robustness to environmental light interference and head movements, and can obtain more accurate estimates of heart rate and respiration rate compared with the existing method.

Key words: imaging photoplethysmography, variational mode decomposition, energy entropy, adaptive de-noising, non-contact measurement, heart rate, respiratory rate