基于压缩感知对心电信号的降噪重构

Electrocardiogram signal denoising and reconstruction based on compressed sensing

由于心电信号具有幅值较小、干扰繁多的特点,利用经典压缩感知方法重构得到的信号往往不能精确反映所要传达的信息。为解决此问题,提出一种基于小波变换的压缩感知算法,先对心电信号进行小波分解,后通过对包含噪声污染较多的高频系数进行降噪和压缩重构处理,最终采用小波逆变换恢复出信号,并且对降噪效果进行数据分析。仿真结果表明,利用小波变换与压缩感知相结合恢复出的信号抑制噪声效果明显,提高了有用信息的完整度,得到了较高的信噪比。

Due to the ElectroCardioGram （ECG） signal has small amplitude and large interference range, the reconstructed signal according to the classical Compressed Sensing （CS） theory cannot be accurately conveyed by the signal. To solve this problem, compressed sensing based on the wavelet transform was stressed on, using the wavelet deeomposition separating the electrocardiogram, reducing noise pollution, compressing and reconstructing the high frequency coefficients, to recover the signal through the wavelet inverse transform, meanwhile analysis on the data effect was made. The simulation result shows that, by combining wavelet transform with compressed sensing to recover the signal, the noise suppressing effect is obvious, the integrity of useful information is enhanced, and a higher Signal-to-Noise Ratio （SNR） is achieved.