We present in this paper an algorithm of filtering the noisy real ECG signal. The classical wavelet denoising process, based on the Donoho et al. algorithm, at the 4th level, appears clearly the P and T waves whereas the R waves undergo considerable distortion. This is due to the interference of the WGN and the free noise ECG detail sequences at level 4. To overcome this drawback, our key idea is to estimate the corrupted WGN and consequently remove the noise interfering R waves at the 4th level detail sequence. Our denoising algorithm was applied to a set of the MIT-BIH Arrhythmia Database ECG records corrupted with a 0 dB WGN which provided an output SNR of around 6 dB and an MSE value of around 0.0011. A comparative analysis using the low pass Butterworth filter and the 4th level classical wavelet denoising provides the output SNR values of around 3 dB and MSE value of around 0.0018; which demonstrates the superior performance of our proposed denoising algorithm.
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机译：我们在本文中展示了一种过滤嘈杂的真实ECG信号的算法。基于Donoho等人的古典小波去噪过程。在第4级的算法显然出现P和T波，而R波发生相当大的失真。这是由于WGN的干扰和在4级的自由噪声ECG细节序列。为了克服这一缺点，我们的关键思想是估计破坏的WGN并因此在第4级细节序列中去除噪声干扰R波。我们的去噪算法应用于一组MIT-BIH心律失常数据库ECG记录，其中0 dB WGN损坏，提供了大约6dB的输出SNR，MSE值约为0.0011。使用低通巴特韦尔滤波器和第四级经典小波去噪的比较分析提供了大约3dB和MSE值约为0.0018的输出SNR值;这证明了我们提出的去噪算法的卓越性能。
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