计算机工程与应用 ›› 2014, Vol. 50 ›› Issue (14): 131-134.

• 数据库、数据挖掘、机器学习 • 上一篇    下一篇

一种高效的PPG压缩感知重构算法

康如婷,赵曙光,刘  浩   

  1. 东华大学 信息科学与技术学院,上海 201620
  • 出版日期:2014-07-15 发布日期:2014-08-04

Higher efficient compressed sensing reconstruction algorithm of PPG signal

KANG Ruting, ZHAO Shuguang, LIU Hao   

  1. School of Science and Technology, Donghua University, Shanghai 201620, China
  • Online:2014-07-15 Published:2014-08-04

摘要: 首先阐述了压缩感知(CS)的理论框架,然后分析了光电容积脉搏波(PPG)信号的稀疏性,最后提出了基于CS理论PPG信号的压缩重构框架。基于此框架采用正交匹配追踪算法和改进的正交匹配追踪算法对已压缩的信号进行重构,实验结果表明,PPG信号长度的选取、压缩比的大小以及观测个数的多少都对重构性能有重要影响。

关键词: 压缩感知, 稀疏性, 正交匹配追踪, 光电容积脉搏波(PPG)信号

Abstract: In this paper, the Compressed Sensing(CS) framework is introduced firstly, and then sparsity of the Photo-Plethysmography(PPG) signal is analyzed. Finally, the PPG signal compression and reconstruction framework based on CS theory is proposed. Via Orthogonal Matching Pursuit(OMP) and Enhanced Orthogonal Matching Pursuit(E-OMP), it is demonstrated that the performance of reconstruction is correlated with the length of the signal, the compression ratio and the number of measurements.

Key words: compressed sensing, sparsity, orthogonal matching pursuit, Photo-Plethysmography(PPG) signal