Literature DB >> 21096226

Reducing electrocardiographic artifacts from electromyogram signals with independent component analysis.

J D Costa Junior1, D D Ferreira, J Nadal, A L Miranda de Sa.   

Abstract

The aim of this work was to reduce ECG artifacts from surface electromyogram (EMG) signals collected from lumbar muscles with the blind source separation technique based on independent component analysis (ICA). Using four EMG signals collected above erector spinal lumbar muscles from 27 subjects, the proposed method fail in separating the sources. However, when considering a single channel of EMG and the same one time-shifted by one sample, the FastICA allowed reducing the signal to ECG noise ratio.

Mesh:

Year:  2010        PMID: 21096226     DOI: 10.1109/IEMBS.2010.5626507

Source DB:  PubMed          Journal:  Annu Int Conf IEEE Eng Med Biol Soc        ISSN: 2375-7477


  3 in total

1.  Performance Analysis of ICA in Sensor Array.

Authors:  Xin Cai; Xiang Wang; Zhitao Huang; Fenghua Wang
Journal:  Sensors (Basel)       Date:  2016-05-05       Impact factor: 3.576

2.  Local Wavelet-Based Filtering of Electromyographic Signals to Eliminate the Electrocardiographic-Induced Artifacts in Patients with Spinal Cord Injury.

Authors:  Matthew Nitzken; Nihit Bajaj; Sevda Aslan; Georgy Gimel'farb; Ayman El-Baz; Alexander Ovechkin
Journal:  J Biomed Sci Eng       Date:  2013-07-18

Review 3.  Comparative Review of the Algorithms for Removal of Electrocardiographic Interference from Trunk Electromyography.

Authors:  Lin Xu; Elisabetta Peri; Rik Vullings; Chiara Rabotti; Johannes P Van Dijk; Massimo Mischi
Journal:  Sensors (Basel)       Date:  2020-08-29       Impact factor: 3.576

  3 in total

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