基于视频放大与盲源分离的非接触式心率检测

非接触式心率(HR)检测可以通过远程光电容积描记术(rPPG)实现,引起越来越多的关注.但在实际应用中,rPPG信号非常细微,极易被噪声淹没,从而导致现有的基于rPPG的心率检测方法很难准确地估计心率.针对以上问题,本文提出了一种增强rPPG信号、抑制噪声的非接触式心率检测方法.在这种方法中,首先通过欧拉颜色放大技术对正常HR分布频带上的色度信息进行放大,避免rPPG信号过小被噪声淹没;接着使用人脸检测与跟踪技术选定合适的感兴趣皮肤区域;然后在感兴趣区域内提取放大后的色度信息,使用盲源分离方法和相关性分析分离出rPPG信号;最后对rPPG信号进行时域滤波与功率谱密度分析,估计出HR值.经多组实验验证,本文所提方法相比于以前方法具有更高的HR估计精度.

Non-Contact Heart Rate Detection Based on Video Amplification and Blind Source Separation

Non-contact Heart Rate (HR) detection can be achieved by remote PhotoPlethysmoGraphy (rPPG), which has attracted more and more attention. However, in practical applications, the rPPG signal is very subtle and easily overwhelmed by noise, which makes it difficult to accurately estimate the HR using existing rPPG-based HR detection methods. In view of the above problems, this paper proposes a non-contact heart rate detection method that enhances rPPG signal and suppresses noise. In this method, the chromaticity information in the normal HR distribution band is first amplified by Euler color amplification technology to avoid the rPPG signal being too small and being overwhelmed by noise; then use face detection and tracking technology to select the appropriate skin of interest Region; then extract the amplified chrominance information in the region of interest, and use the blind source separation method and correlation analysis to separate the rPPG signal; finally, the rPPG signal is time-domain filtered and power spectral density analysis to estimate the HR value. Multiple experiments show that the proposed method has higher HR estimation accuracy than previous methods.