CAJ | 학술논문

为校正ECG信号的基陑漂移，提出小波变换和自适应滤波陒结合的方法。利用小波变换对原始ECG信号进行分解，将得到的高频分量作为参考信号输入，采用基于幂函数的最小均方算法(P-LMS)进行自适应滤噪处理。通过与传统的归一化最小均方算法(NLMS)进行对比，验证该算法的准确性。仿真实验和MIT-BIH数据库中的实际数据检验结果表明，基于幂函数的最小均方算法和小波变换陒结合的方法能够有效校正基陑漂移，并较好地保持心电信号的几何特征。
위교정ECG신호적기이표이，제출소파변환화자괄응려파희결합적방법。이용소파변환대원시ECG신호진행분해，장득도적고빈분량작위삼고신호수입，채용기우멱함수적최소균방산법(P-LMS)진행자괄응려조처리。통과여전통적귀일화최소균방산법(NLMS)진행대비，험증해산법적준학성。방진실험화MIT-BIH수거고중적실제수거검험결과표명，기우멱함수적최소균방산법화소파변환희결합적방법능구유효교정기이표이，병교호지보지심전신호적궤하특정。
In order to calibrate the baseline shift of ECG signal, the combination methods of wavelet transform and adaptive filtering are proposed. The wavelet transform method is used to decompose the original ECG signal and the high-frequency components are used as reference input data. A new adaptive filtering algorithm, P-LMS based on the power function is proposed to conduct adaptive noise filtering. Compared with the traditional Normalized Least Mean Square(NLMS) algorithm, the proposed algorithm is precise. Using the simulated experiment and actual data in the MIT-BIH database, the method of combining P-LMS and wavelet transform is verified that can effectively correct the baseline shift and maintain the geometric characteristics of the ECG signal.