论文阅读和复现：去除PPG运动伪影的IEEE论文

论文阅读和代码复现：
《Combining Nonlinear Adaptive Filtering and Signal Decomposition for Motion Artifact Removal in Wearable Photoplethysmography》

基本介绍：

由于手腕运动造成的噪声：运动伪影，使得PPG方法的心率监测不准，去除运动伪影噪声在智能手表中是一个难点。

论文中使用的开源数据：PPG database used in 2015 IEEE Signal Processing Cup[1]

[1]Pace and Bricout, “Low Heart Rate Response of Children with Autism Spectrum Disorders in Comparison to Controls during Physical Exercise,” Physiology & Behavior, vol.141, pp.63-68, 2015.

目前已经有的研究：

• 使用独立成分分析ICA

ICA有一个关键的统计独立或不相关假设[11]。因此，在许多实际场景中，将MA与PPG信号分离的结果并不令人满意。

[11]J. Yao and S. Warren, “A short study to assess the potential of independent component analysis for motion artifact separation in wearable pulse oximeter signals,” in Proc. 27th Annual Conf IEEE Engg. Medicine and Biology, pp. 3585-3588, 2005.

• 使用自适应滤波

通过适当设计参考信号，在某些情况下可以达到令人满意的效果。然而，一个设计不好的参考信号会导致较差的MA去除性能。此外，原始PPG信号中的MA与参考信号之间的关系可能不是线性相关的，而是非线性相关的，当选择同步加速度信号作为参考信号时。

[12] Comtois Gary, Yitzhak Mendelson, and Piyush Ramuka, “A Comparative Evaluation of Adaptive Noise Cancellation Algorithms for Minimizing Motion Artifacts in a Forehead-Mounted Wearable Pulse Oximeter,” 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp.1528-1531, 2007.
[13] A. B. Barreto, L. M. Vicente, and I. K. Persad, “Adaptive Cancellation of Motion Artifact in Photoplethysmographic Blood Volume Pulse Measurements for Exercise Evaluation,” Engineering in Medicine and Biology Society, IEEE 17th Annual Conference, vol.2, pp.983-984. 1995.
[14] Ram, M. Raghu, et al. “A novel approach for motion artifact reduction in PPG signals based on AS-LMS adaptive filter.” IEEE Transactions on Instrumentation and Measurement, pp. 1445-1457, 2012.
[15] Hyonyoung Han and Jung Kim, “Artifacts in wearable photoplethysmographs during daily life motions and their reduction with least meansquare based active noise cancellation method,” Computers in Biology and Medicine 42, pp. 387-393, 2012.
[16] Asada, H. Harry, Hong-Hui Jiang, and Peter Gibbs, “Active noise cancellation using MEMS accelerometers for motion-tolerant wearable bio-sensors,” Engineering in Medicine and Biology Society, 2004. IEMBS’04. 26th Annual International Conference of the IEEE. vol. 1, 2004.

• 使用信号分解

信号分解[17]，[18]最近被证明是一种有效的去除MA的方法。例如，在[17]中，作者使用奇异谱分析(SSA)将原始PPG分解为多个分量，然后使用同步加速度信号的信息来识别与MA相关的分量。去除这些分量后，利用剩余分量重构PPG信号，得到更清晰的PPG信号。同样，在[18]中，使用经验模态分解(EMD)将一个原始PPG信号分解为许多分量，并使用同步加速度信号的频谱进行频谱减法去除与MA相关的分量。然而，信号分解通常具有较大的计算量，这可能会阻碍其在低功耗可穿戴设备中的应用。

[17] Z. Zhang, Z. Pi, and B. Liu, “TROIKA: A general framework for heart rate monitoring using wrist-type photoplethysmographic signals during intensive physical exercise,” IEEE Transactions on Biomedical Engineering, vol. 62, no. 2, pp. 522-531, 2015.

[18] Y. Zhang, B. Liu, Z. Zhang, “Combining Ensemble Empirical Mode Decomposition with Spectrum Subtraction Technique for Heart Rate Monitoring Using Wrist-Type Photoplethysmography,” Biomedical Signal Processing and Control, vol. 21, pp. 119-125, 2015.

论文的算法方案