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Titolo:
Removing artifacts from electrocardiographic signals using independent components analysis
Autore:
Barros, AK; Mansour, A; Ohnishi, N;
Indirizzi:
RIKEN, BMC Res Ctr, Aichi 4630003, Japan RIKEN Aichi Japan 4630003RIKEN, BMC Res Ctr, Aichi 4630003, Japan
Titolo Testata:
NEUROCOMPUTING
fascicolo: 1-3, volume: 22, anno: 1998,
pagine: 173 - 186
SICI:
0925-2312(199811)22:1-3<173:RAFESU>2.0.ZU;2-9
Fonte:
ISI
Lingua:
ENG
Soggetto:
SOURCE SEPARATION; NEURAL NETWORKS; DECORRELATION; ALGORITHMS;
Keywords:
independent component analysis; blind separation; adaptive filtering; cardiac artifacts; ECG analysis;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
Citazioni:
22
Recensione:
Indirizzi per estratti:
Indirizzo: Barros, AK RIKEN, BMC Res Ctr, 2271-130 Ana Gahora, Aichi 4630003, Japan RIKEN 2271-130 Ana Gahora Aichi Japan 4630003 i 4630003, Japan
Citazione:
A.K. Barros et al., "Removing artifacts from electrocardiographic signals using independent components analysis", NEUROCOMPUT, 22(1-3), 1998, pp. 173-186

Abstract

In this work, we deal with the elimination of artifacts (electrodes, muscle, respiration, etc.) from the electrocardiographic (ECG) signal. We use a new tool called independent component analysis (ICA) that blindly separatesmixed statistically independent signals. ICA can separate the signal from the interference, even if both overlap in frequency. In order to estimate the mixing parameters in real time, we propose a self-adaptive step-size, derived from the study of the averaged behavior of those parameters, and a! two-layers neural network. Simulations were carried out to show the performance of the algorithm using a standard ECG database. (C) 1998 Elsevier Science B.V. All rights reserved.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 09/07/20 alle ore 14:20:18