Duan Chengcheng, Liang Xiangyang, Dai Fei
School of Defence Science and Technology, Xi'an Technological University, Xi'an 710021, China.
School of Computer Science and Engineering, Xi'an Technological University, Xi'an 710021, China.
Sensors (Basel). 2025 Jan 16;25(2):501. doi: 10.3390/s25020501.
A solution to address the issues of environmental light interference in Remote Photoplethysmography (rPPG) methods is proposed in this paper. First, signals from the face's region of interest (ROI) and background noise signals are simultaneously collected, and the two signals are processed by a differential to obtain a more accurate rPPG signal. This method effectively suppresses background noise and enhances signal quality. Secondly, the singular spectrum analysis algorithm (SSA) is enhanced to further improve the accuracy of heart rate detection. The algorithm's parameters are adaptively optimized by integrating the spectral and periodic characteristics of the heart rate signal. Experimental results demonstrate that the method proposed in this paper effectively mitigates the effects of lighting changes on heart rate detection, thereby enhancing detection accuracy. Overall, the experiments indicate that the proposed method significantly improves the effectiveness and accuracy of heart rate detection, achieving a high level of consistency with existing contact-based detection methods.
本文提出了一种解决远程光电容积脉搏波描记法（rPPG）中环境光干扰问题的方案。首先，同时采集来自面部感兴趣区域（ROI）的信号和背景噪声信号，并通过差分对这两个信号进行处理，以获得更准确的rPPG信号。该方法有效地抑制了背景噪声并提高了信号质量。其次，对奇异谱分析算法（SSA）进行了改进，以进一步提高心率检测的准确性。通过结合心率信号的频谱和周期性特征，对算法参数进行自适应优化。实验结果表明，本文提出的方法有效地减轻了光照变化对心率检测的影响，从而提高了检测准确性。总体而言，实验表明，所提出的方法显著提高了心率检测的有效性和准确性，与现有的基于接触的检测方法具有高度一致性。
