Dengyong Zhang1,2, Minzhi Yuan1,2, Feng Li1,2, Lebing Zhang3,*, Yanqiang Sun4, Yiming Ling5
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2809-2824, 2024, DOI:10.32604/cmes.2023.029181
Abstract Electrocardiogram (ECG) signal is one of the noninvasive physiological measurement techniques commonly used in cardiac diagnosis. However, in real scenarios, the ECG signal is susceptible to various noise erosion, which affects the subsequent pathological analysis. Therefore, the effective removal of the noise from ECG signals has become a top priority in cardiac diagnostic research. Aiming at the problem of incomplete signal shape retention and low signal-to-noise ratio (SNR) after denoising, a novel ECG denoising network, named attention-based residual dense shrinkage network (ARDSN), is proposed in this paper. Firstly, the shallow ECG characteristics are extracted by a shallow feature extraction network… More >
Login
Register
