计算机应用与软件2024，Vol.41Issue(5)：40-48,9.DOI:10.3969/j.issn.1000-386x.2024.05.007
基于深度全卷积提升网络的心电信号降噪
ECG SIGNAL DENOISING BASED ON DEEP FULLY CONVOLUTIONAL BOOSTING NETWORK
摘要
Abstract
The traditional method of denoise is difficult to accurately remove the complex noise without losing the ECG signal,an ECG signal denoising method is proposed based on the deep full convolutional Boosting network(FCBN).This method used the characteristics of the local connection of the full convolutional network to retain the detailed information of the ECG signal waveform,and stacked multiple FCN networks through the Boosting algorithm to form a deep neural network.The original signal in multiple stages were inputted,and it retained the deep information of the ECG signal features to improve the denoising performance of the overall network.Experimental results show that compared with wavelet threshold method,S transform method,BPNN method and convolutional autoencoder,this method has obvious improvement in SNR and smaller RMSE,while retaining more ECG signal waveforms morphological information.关键词
心电信号/降噪/全卷积网络/提升算法Key words
ECG signal/Denoising/Fully convolutional network/Boosting algorithm分类
信息技术与安全科学引用本文复制引用
杨畅,刘慧妍,刘明..基于深度全卷积提升网络的心电信号降噪[J].计算机应用与软件,2024,41(5):40-48,9.基金项目
国家自然科学基金项目(61703133,61673158) （61703133,61673158）
河北省自然科学基金项目(F2018201070) （F2018201070）
河北省青年拔尖项目(BJ2019044). （BJ2019044）
