Singh Omkar, Sunkaria Ramesh Kumar
Department of Electronics and Communication Engineering, Dr B. R Ambedkar National Institute of Technology, Jalandhar, Punjab, 144 011, India.
Australas Phys Eng Sci Med. 2017 Mar;40(1):219-229. doi: 10.1007/s13246-016-0510-6. Epub 2016 Dec 29.
This paper presents new methods for baseline wander correction and powerline interference reduction in electrocardiogram (ECG) signals using empirical wavelet transform (EWT). During data acquisition of ECG signal, various noise sources such as powerline interference, baseline wander and muscle artifacts contaminate the information bearing ECG signal. For better analysis and interpretation, the ECG signal must be free of noise. In the present work, a new approach is used to filter baseline wander and power line interference from the ECG signal. The technique utilized is the empirical wavelet transform, which is a new method used to compute the building modes of a given signal. Its performance as a filter is compared to the standard linear filters and empirical mode decomposition.The results show that EWT delivers a better performance.
本文提出了使用经验小波变换(EWT)对心电图(ECG)信号进行基线漂移校正和降低电力线干扰的新方法。在心电图信号的数据采集过程中,诸如电力线干扰、基线漂移和肌肉伪迹等各种噪声源会污染携带信息的心电图信号。为了更好地进行分析和解读,心电图信号必须无噪声。在当前工作中,采用了一种新方法来从心电图信号中滤除基线漂移和电力线干扰。所使用的技术是经验小波变换,它是一种用于计算给定信号的构造模式的新方法。将其作为滤波器的性能与标准线性滤波器和经验模态分解进行了比较。结果表明,经验小波变换具有更好的性能。