基于振动相位信号分解的非接触式心率检测

心率是反映人体心血管系统状态的重要依据.基于视频的非接触式心率检测凭借其场景适应能力强、成本低等优势,得到了广泛应用.然而,这种检测方法容易受到光照变化、目标运动等噪声干扰.针对该问题,本文提出了一种基于振动相位信号分解的腕部表皮视频心率提取方法,其核心思想是设计方向选择的复可控金字塔搜索出脉搏信号的带通范围,使用信噪比进行脉搏信号的感兴趣选择,使用鲁棒主成分分析从混合信号中分离出脉搏信号,从而最终实现脉搏信号抗噪的心率检测.本文自行采集了心率检测数据集,并使用脉搏检测仪作为真值进行方法验证.在干扰场景下准确率为97.80％,与3种主流方法对比准确率提升均大于5％.

Non-Contact Heart Rate Detection Based on Decomposition of Vibration Phase Signals

Heart rate is an important basis for reflecting the status of the cardiovascular system in humans. Video-based non-contact heart rate detection has been widely applied due to its advantages of strong scene adaptability and low cost. However, this method is susceptible to noise interference such as illumination change and target movement. To solve this problem, this study proposes a method based on the decomposition of vibration phase signals to extract the video heart rate on the wrist skin. Its core idea is to find the band range of pulse signals by designing a direction-selective complex steerable pyramid. The signal-to-noise ratio is used to select the pulse signals of interest and the robust principal component analysis is employed to isolate pulse signals from the mixed signals. Finally, the heart rate of noise-resistant pulse signals is detected. In this study, the data set of heart rate detection is collected, and the output from a pulse detector is taken as the true values to verify the method. The accuracy is 97.80% in the interference scene, which is over 5% higher than that of the three mainstream methods.