基于压缩感知的PPG信号处理算法性能研究  

Research on performance of PPG signal processing algorithm based on compressed sensing

作　　者：黄芳 刘海洋[1] 陈立平[1] 张浩[1] HUANG Fang;LIU Haiyang;CHEN Liping;ZHANG Hao(Institute of Microelectronics of Chinese Academy of Sciences,Beijing 100029,China;University of Chinese Academy of Sciences,Beijing 100049,China)

机构地区：[1]中国科学院微电子研究所,北京100029 [2]中国科学院大学,北京100049

出　　处：《电子设计工程》2021年第15期1-5,共5页Electronic Design Engineering

基　　金：国家科技重大专项(01专项)资助(2018ZX01031201);国家科技重大专项(09专项)资助(2018ZX09201011)。

摘　　要：随着移动健康医疗应用的快速发展,压缩感知(CS)已用于PPG信号处理。信号恢复过程是基于CS的PPG信号处理中重要的步骤,文中对用于PPG信号处理的4种典型压缩感知恢复算法即正交匹配追踪(OMP)算法、压缩采样匹配追踪(CoSaMP)算法、基追踪(BP)算法和块稀疏贝叶斯学习(BSBL)算法进行综合性能分析,总结出算法在PPG信号处理上的优缺点,为实际应用提供研究参考。结果表明,BSBL的性能优于其他算法,其抗干扰性最强、信号恢复质量最好,OMP算法性能在不同压缩比下最稳定。BSBL算法的信噪比能达到OMP算法的5倍。CoSaMP算法与OMP算法的性能受压缩比影响相近,但综合性能更优。With the rapid development of mobile health care applications,Compressed Sensing(CS)has been used for PPG signal processing.The signal recovery process is an important step in the processing of CS-based PPG signals.In this paper,four typical recovery algorithms which used for the comprehensive performance analysis of PPG signal processingwill be analyzed in an comprehensive way,including Orthogonal Matching Pursuit(OMP)algorithm,Compressed Sampling Matching Pursuit(CoSaMP)algorithm,base tracking(BP)algorithm and Block Sparse Bayesian learning(BSBL)algorithm.The advantages and disadvantages of the algorithm in PPG signal processing will be summarized to provide a research reference for practical applications.The results show that the performance of BSBL is better thananyother algorithms,especially the strongest anti-interference and the best signal recovery quality.The performance of OMP algorithm is the most stable under different compression ratios.The signal-to-noise ratio of the BSBL algorithm can reach 5 times that of the OMP algorithm.The performance affected by compression ratioof CoSaMP algorithm andis similar to OMP algorithm,but CoSaMP algorithm’s overall performance is better.

关 键 词：压缩感知 移动医疗 算法性能 PPG信号 

分 类 号：TN911.7[电子电信—通信与信息系统]