CASIA OpenIR  > 复杂系统管理与控制国家重点实验室  > 先进机器人
A stacked contractive denoising auto-encoder for ECG signal denoising
Xiong, Peng1; Wang, Hongrui1,2; Liu, Ming2; Lin, Feng3; Hou, Zengguang4; Liu, Xiuling2
Source PublicationPHYSIOLOGICAL MEASUREMENT
2016-12-01
Volume37Issue:12Pages:2214-2230
SubtypeArticle
AbstractAs a primary diagnostic tool for cardiac diseases, electrocardiogram ( ECG) signals are often contaminated by various kinds of noise, such as baseline wander, electrode contact noise and motion artifacts. In this paper, we propose a contractive denoising technique to improve the performance of current denoising auto-encoders (DAEs) for ECG signal denoising. Based on the Frobenius norm of the Jacobean matrix for the learned features with respect to the input, we develop a stacked contractive denoising auto-encoder (CDAE) to build a deep neural network (DNN) for noise reduction, which can significantly improve the expression of ECG signals through multi-level feature extraction. The proposed method is evaluated on ECG signals from the bench-marker MIT-BIH Arrhythmia Database, and the noises come from the MIT-BIH noise stress test database. The experimental results show that the new CDAE algorithm performs better than the conventional ECG denoising method, specifically with more than 2.40 dB improvement in the signal-to-noise ratio (SNR) and nearly 0.075 to 0.350 improvements in the root mean square error (RMSE).
KeywordElectrocardiogram (Ecg) Denoising Auto-encoder (Dae) Baseline Wander Motion Artifacts Electrode Contact Noise
WOS HeadingsScience & Technology ; Life Sciences & Biomedicine ; Technology
DOI10.1088/0967-3334/37/12/2214
WOS KeywordFILTERING FRAMEWORK ; AUTOENCODERS ; NETWORKS
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(61473112) ; Foundation for Distinguished Young Scholars of Hebei Province(F2016201186) ; Natural Science Foundation of Hebei Province(F2015201112) ; Science and Technology Research Project for Universities and Colleges in Hebei Province(ZD2015067)
WOS Research AreaBiophysics ; Engineering ; Physiology
WOS SubjectBiophysics ; Engineering, Biomedical ; Physiology
WOS IDWOS:000389324000003
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/13359
Collection复杂系统管理与控制国家重点实验室_先进机器人
Affiliation1.Yanshan Univ, Coll Elect & Informat Engn, Qinhuangdao, Peoples R China
2.Hebei Univ, Key Lab Digital Med Engn Hebei Prov, Coll Elect & Informat Engn, Baoding, Peoples R China
3.Nanyang Technol Univ, Sch Comp Engn, Singapore, Singapore
4.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Xiong, Peng,Wang, Hongrui,Liu, Ming,et al. A stacked contractive denoising auto-encoder for ECG signal denoising[J]. PHYSIOLOGICAL MEASUREMENT,2016,37(12):2214-2230.
APA Xiong, Peng,Wang, Hongrui,Liu, Ming,Lin, Feng,Hou, Zengguang,&Liu, Xiuling.(2016).A stacked contractive denoising auto-encoder for ECG signal denoising.PHYSIOLOGICAL MEASUREMENT,37(12),2214-2230.
MLA Xiong, Peng,et al."A stacked contractive denoising auto-encoder for ECG signal denoising".PHYSIOLOGICAL MEASUREMENT 37.12(2016):2214-2230.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Xiong, Peng]'s Articles
[Wang, Hongrui]'s Articles
[Liu, Ming]'s Articles
Baidu academic
Similar articles in Baidu academic
[Xiong, Peng]'s Articles
[Wang, Hongrui]'s Articles
[Liu, Ming]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Xiong, Peng]'s Articles
[Wang, Hongrui]'s Articles
[Liu, Ming]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.