Weng Binwei, Blanco-Velasco Manuel, Barner Kenneth E
Dept. of Electrical & Computer Engineering, University of Delaware, Newark, DE 19716, USA.
Conf Proc IEEE Eng Med Biol Soc. 2006;2006:1-4. doi: 10.1109/IEMBS.2006.259340.
The electrocardiogram (ECG) has been widely used for diagnosis purposes of heart diseases. Good quality ECG are utilized by the physicians for interpretation and identification of physiological and pathological phenomena. However, in real situations, ECG recordings are often corrupted by artifacts. One prominent artifact is the high frequency noise caused by electromyogram induced noise, power line interferences, or mechanical forces acting on the electrodes. Noise severely limits the utility of the recorded ECG and thus need to be removed for better clinical evaluation. Several methods have been developed for ECG denoising. In this paper, we proposed a new ECG denoising method based on the recently developed Empirical Mode Decomposition (EMD). The proposed EMD-based method is able to remove high frequency noise with minimum signal distortion. The method is validated through experiments on the MIT-BIH database. Both quantitative and qualitative results are given. The results show that the proposed method provides very good results for denoising.
心电图(ECG)已被广泛用于心脏病的诊断。医生利用高质量的心电图来解释和识别生理和病理现象。然而,在实际情况中,心电图记录常常会受到伪迹的干扰。一种突出的伪迹是由肌电图诱导噪声、电力线干扰或作用于电极的机械力引起的高频噪声。噪声严重限制了记录的心电图的效用,因此需要去除噪声以进行更好的临床评估。已经开发了几种用于心电图去噪的方法。在本文中,我们提出了一种基于最近开发的经验模态分解(EMD)的新的心电图去噪方法。所提出的基于EMD的方法能够以最小的信号失真去除高频噪声。该方法通过在MIT-BIH数据库上进行实验得到验证。给出了定量和定性结果。结果表明,所提出的方法在去噪方面提供了非常好的结果。