Literature DB >> 17281286

Limitations of ICA for Artefact Removal.

Djuwari Djuwari1, Dinesh Kant Kumar, Marimuthu Palaniswami.   

Abstract

This paper reports analysis of the limitations of using Independent Component Analysis (ICA) for biosignal analysis especially artefact removal. The possible difficulty is that there are limited number of electrodes (recordings) making it an overcomplete problem (non-square ICA). The other difficulty is the distribution of biosignal being close to Gaussian. These two properties of the signals may make these outside the standard ICA application. This paper reports that ICA is able to successfully separate the biosignals if the number of recordings are not less than the number of sources. If that is not the case, ICA separates artefact component only when the corresponding artefact is predominant. The experiments demonstrate that the results are not reliable and hence the authors recommend that caution should be exercised before using ICA for such applications.

Entities:  

Year:  2005        PMID: 17281286     DOI: 10.1109/IEMBS.2005.1615516

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  4 in total

1.  Remote photoplethysmography with constrained ICA using periodicity and chrominance constraints.

Authors:  Richard Macwan; Yannick Benezeth; Alamin Mansouri
Journal:  Biomed Eng Online       Date:  2018-02-09       Impact factor: 2.819

2.  Effective automated method for detection and suppression of muscle artefacts from single-channel EEG signal.

Authors:  Manali Saini; Udit Satija; Madhur Deo Upadhayay
Journal:  Healthc Technol Lett       Date:  2020-04-14

3.  Improved Cognitive Vigilance Assessment after Artifact Reduction with Wavelet Independent Component Analysis.

Authors:  Nadia Abu Farha; Fares Al-Shargie; Usman Tariq; Hasan Al-Nashash
Journal:  Sensors (Basel)       Date:  2022-04-15       Impact factor: 3.847

4.  Adaptive algorithm utilizing acceptance rate for eliminating noisy epochs in block-design functional near-infrared spectroscopy data: application to study in attention deficit/hyperactivity disorder children.

Authors:  Stephanie Sutoko; Yukifumi Monden; Tsukasa Funane; Tatsuya Tokuda; Takusige Katura; Hiroki Sato; Masako Nagashima; Masashi Kiguchi; Atsushi Maki; Takanori Yamagata; Ippeita Dan
Journal:  Neurophotonics       Date:  2018-10-11       Impact factor: 3.593

  4 in total

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