电子学报 ›› 2017, Vol. 45 ›› Issue (7): 1646-1652.DOI: 10.3969/j.issn.0372-2112.2017.07.014

• 学术论文 • 上一篇    下一篇

基于联合稀疏谱重构的PPG信号降噪算法

熊继平1, 蒋定德2, 蔡丽桑1, 汤清华1, 何小卫1   

  1. 1. 浙江师范大学数理与信息工程学院, 浙江金华 321004;
    2. 东北大学计算机科学与工程学院, 辽宁沈阳 110819
  • 收稿日期:2015-11-12 修回日期:2016-04-11 出版日期:2017-07-25
    • 作者简介:
    • 熊继平,男,浙江师范大学数理与信息工程学院副教授,研究生导师,研究方向为压缩感知算法及应用.E-mail:xjping@zjnu.cn;蒋定德,男,博士,东北大学计算机科学与工程学院教授,博士生导师,主要研究方向为网络测量、网络安全、软件定义网络和认知网络等.E-mail:jiangdd@mail.neu.edu.cn;蔡丽桑,女,浙江师范大学数理与信息工程学院硕士研究生,研究方向稀疏信息处理和压缩感知.E-mail:574585714@qq.com;何小卫,男,浙江师范大学数理与信息工程学院副教授,民盟浙师大委员会在职总支第一支部主委.研究方向模糊系统与粗糙集、计算机应用.E-mail:jhhxw@zjnu.cn
    • 基金资助:
    • 浙江省自然科学基金 (No.LY14F010008); 国家自然科学基金 (No.61572023)

An Algorithm of Motion Artifact Reduction in PPG Signals Based on Joint Sparse Spectrum Reconstruction

XIONG Ji-ping1, JIANG Ding-de2, CAI Li-sang1, TANG Qing-hua1, HE Xiao-wei1   

  1. 1. College of Mathematics, Physics and Information Engineering, Zhejiang Normal University, Jinhua, Zhejiang 321004, China;
    2. College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110819
  • Received:2015-11-12 Revised:2016-04-11 Online:2017-07-25 Published:2017-07-25
    • Supported by:
    • National Natural Science Foundation of Zhejiang Province,  China (No.LY14F010008); National Natural Science Foundation of China (No.61572023)

摘要:

针对光电容积脉搏波(Photoplethysmography,PPG)传感器数据采集降噪问题,本文提出一种基于联合稀疏重构的PPG信号运动噪声降噪算法.该算法通过构建同时间段内PPG信号和加速度信号的频谱矩阵,提取频谱矩阵稀疏特征和该矩阵行稀疏特征,利用压缩感知方法,将PPG信号运动噪声去除过程建模为联合稀疏信号重构过程,并将该过程进一步建模为最优化模型,通过迭代寻优来获得该模型的最优解,结合谱减法,从而有效去除PPG信号中的运动噪声,降低噪声对PPG信号的影响.仿真分析表明,本文提出的算法能有效去除PPG信号中的运动噪声,获得较好的降噪效果.

关键词: 光电容积脉搏波, 心率测量, 稀疏信号重构, 压缩感知

Abstract:

This paper proposes a joint sparse spectrum reconstruction-based motion artifact reduction algorithm for Photoplethysmo-graphy (PPG) signals to overcome the artifact removing problem in the PPG sensor data collection.Firstly,our algorithm constructs a spectral matrix,using PPG signals and acceleration signals during the same time period.The sparse characteristics of the spectral matrix and its rows are extracted.Secondly,we use the compressive sensing to model the motion artifact removing process in PPG signals as a joint sparse signal reconstruction process.Then this process is further modeled as an optimal model.We exploit the iterative method to obtain the optimal solution to the model.Finally,we combine the spectrum subtraction to remove the motion artifact in PPG signals.In the result,we can effectively decrease the impact of the motion artifact on PPG signals.Simulation results demonstrate that the algorithm proposed in this paper can effectively remove the motion artifact in PPG signals and attain the better noise reduction performance.

Key words: photoplethysmography (PPG), heart rate monitoring, sparse signal reconstruction, compressive sensing

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