Ayat Mohammad, Shamsollahi Mohammad B, Mozaffari Behrooz, Kharabian Shahrzad
Biomedical Signal and Image Processing Laboratory (BiSIPL) School of Electrical Engineering Sharif University of Technology, Iran.
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:416-9. doi: 10.1109/IEMBS.2009.5332617.
ECG denoising has always been an important issue in medical engineering. The purposes of denoising are reducing noise level and improving signal to noise ratio (SNR) without distorting the signal. This paper proposes a method for removing white Gaussian noise from ECG signals. The concepts of singularity and local maxima of the wavelet transform modulus were used for analyzing singularity and reconstructing the ECG signal. Adaptive thresholding was used to remove white Gaussian noise modulus maximum of wavelet transform and then reconstruct the signal.
心电图去噪一直是医学工程中的一个重要问题。去噪的目的是在不扭曲信号的情况下降低噪声水平并提高信噪比（SNR）。本文提出了一种从心电图信号中去除白高斯噪声的方法。利用小波变换模的奇异性和局部极大值的概念来分析奇异性并重建心电图信号。采用自适应阈值法去除小波变换模最大值处的白高斯噪声，然后重建信号。
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