ECG signal enhancement based on improved denoising auto-encoder

CORC > 自动化研究所 > 中国科学院自动化研究所 > 复杂系统管理与控制国家重点实验室 > 先进机器人控制团队

	ECG signal enhancement based on improved denoising auto-encoder
	Xiong, Peng 1; Wang, Hongrui 1,2; Liu, Ming 2; Zhou, Suiping 3; Hou, Zengguang4 ; Liu, Xiuling 2
刊名	ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
	2016-06-01
卷号	52 页码:194-202
关键词	Denoising auto-encoder (DAE) ECG signal denoising Wavelet transform (WT) Deep neural network (DNN)
英文摘要	The electrocardiogram (ECG) is a primary diagnostic tool for examining cardiac tissue and structures. ECG signals are often contaminated by noise, which can manifest with similar morphologies as an ECG waveform in, the frequency domain. In this paper, a novel deep neural network (DNN) is proposed to solve the above mentioned problem. This DNN is created from an improved denoising auto-encoder (DAE) reformed by a wavelet transform (WT), method. A WT with scale-adaptive thresholding method is used to filter most of the noise. A DNN based on improved DAE is then used to remove any residual noise, which is often complex with an unknown distribution in the frequency domain. The proposed method was evaluated on ECG signals from the MIT-BIH Arrhythmia database, and added noise signals were obtained from the MIT-BIH Noise Stress Test database. The results show that the,average of output signal-to-noise ratio (SNR) is from 21.56 dB to 22.96 dB, and the average of root mean square error (RMSE) is less than 0.037. The proposed method showed significant improvement in SNR and RMSE compared with the individual processing with either a WT or DAE, thus providing promising approaches for ECG signal enhancement (C) 2016 Elsevier Ltd. All rights reserved.
WOS标题词	Science & Technology ; Technology
类目[WOS]	Automation & Control Systems ; Computer Science, Artificial Intelligence ; Engineering, Multidisciplinary ; Engineering, Electrical & Electronic
研究领域[WOS]	Automation & Control Systems ; Computer Science ; Engineering
关键词[WOS]	ADAPTIVE KALMAN FILTER ; NEURAL-NETWORKS
收录类别	SCI
语种	英语
WOS记录号	WOS:000379631100018
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/12156]
专题	自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队
作者单位	1.Yanshan Univ, Coll Elect & Informat Engn, Qinhuangdao, Peoples R China 2.Hebei Univ, Coll Elect & Informat Engn, Key Lab Digital Med Engn Hebei Prov, Baoding, Peoples R China 3.Middlesex Univ, Sch Sci & Technol, London N17 8HR, England 4.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Xiong, Peng,Wang, Hongrui,Liu, Ming,et al. ECG signal enhancement based on improved denoising auto-encoder[J]. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE,2016,52:194-202.
APA	Xiong, Peng,Wang, Hongrui,Liu, Ming,Zhou, Suiping,Hou, Zengguang,&Liu, Xiuling.(2016).ECG signal enhancement based on improved denoising auto-encoder.ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE,52,194-202.
MLA	Xiong, Peng,et al."ECG signal enhancement based on improved denoising auto-encoder".ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 52(2016):194-202.