基于小波分析的呼吸信号消噪方法研究

Research on Denoising Methods of Respiratory Signal Based on Wavelet Analysis

  • 摘要: 为搭建呼吸信号采集平台,利用小波分析对流量传感器采集的呼吸信号进行了滤波处理. 实验中,讨论了小波基函数、分解层数以及阈值准则对小波消噪效果的影响,并得到了分析信号的最优小波基函数和最优分解层数. 基于组件对象模型(COM)技术,运用VC++和Matlab联合编程,形成可脱离Matlab环境运行的可执行文件. 仿真结果表明,信号采集平台成功实现了呼吸信号的采集与消噪,并取得了较好的效果.

     

    Abstract: For building respiratory signal acquisition platform, the respiratory signal obtained by flow-sensor was denoised using wavelet analysis. The relation between selection of wavelet function, decomposition order and threshold and the quality of wavelet filtering was analyzed through simulation, and the optimal wavelet function and decomposition order was obtained. Lastly, respiratory signal was acquired and filtered by the executable-file running independent of Matlab successfully, which was realized by the mixed program between VC++ and Matlab utilizing COM technology of Matlab, and the simulation results was better.

     

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