CAJ | 학술논문

实测的心电信号不可避免地存在一些强干扰和噪声,如何在强背景干扰和噪声下准确提取出有用的心电信号, 是心脏病智能诊断的一个重要内容.提出一种新的基于小波熵的弱心电信号去噪方法,先将信号小波分解,再对不同分解尺度上的高频系数进行小波熵阈值的量化处理,然后利用最高一层小波分解的低频系数分量和经过阈值处理的不同尺度的高频小波系数分量,组成进行信号重构所需要的系数分量进行重构,将严重的干扰和噪声去掉,实现有效信号的提取.最后分别利用临床的实测心电数据和MIT/BIH心电数据库信号进行验证,并针对不同噪声类型和不同信噪比情况进行分析.结果表明,该方法简单有效,尤其对于高频噪声效果更优,且适于实际应用.
실측적심전신호불가피면지존재일사강간우화조성,여하재강배경간우화조성하준학제취출유용적심전신호, 시심장병지능진단적일개중요내용.제출일충신적기우소파적적약심전신호거조방법,선장신호소파분해,재대불동분해척도상적고빈계수진행소파적역치적양화처리,연후이용최고일층소파분해적저빈계수분량화경과역치처리적불동척도적고빈소파계수분량,조성진행신호중구소수요적계수분량진행중구,장엄중적간우화조성거도,실현유효신호적제취.최후분별이용림상적실측심전수거화MIT/BIH심전수거고신호진행험증,병침대불동조성류형화불동신조비정황진행분석.결과표명,해방법간단유효,우기대우고빈조성효과경우,차괄우실제응용.
There are inevitably strong disturbance and noise in the measured ECG signal. How to extract the ECG wave accurately with strong background disturbance and noise is an important part in the intelligent diagnosis of heart disease. In this paper, a new method based on wavelet entropy was presented. Firstly, the signal was disposed of wavelet decomposition. Secondly, the high-frequency wavelet decomposition coefficients of different scale was processed with wavelet entropy thresholds and quantification. Then the low-frequency coefficients of the highest level wavelet decomposition and the high-frequency wavelet coefficients of the different scales after the threshold processing were composed into the wavelet coefficients component for reconstruction. Then the serious disturbance and noise were removed and the signal was extracted. The proposed method was verified using the clinical data and the data from MIT-BIH arrhythmia database. The different noise types with different SNR was analyzed. The results indicated that this method was simple, effective, accurate, especially for removing high-frequency noise.