Literature DB >> 11459613

Removal of ECG interference from the EEG recordings in small animals using independent component analysis.

S Tong1, A Bezerianos, J Paul, Y Zhu, N Thakor.   

Abstract

In experiments involving small animals, the electroencephalogram (EEG) recorded during severe injury and accompanying resuscitation exhibit the strong presence of electrocardiogram (ECG). For improved quantitative EEG (qEEG) analysis, it is therefore imperative to remove ECG interference from EEG. In this paper, we validate the use of independent component analysis (ICA) to effectively suppress the interference of ECG from EEG recordings during normal activity, asphyxia and recovery following asphyxia. Two channels of EEG from five rats were recorded continuously for 2 h. Simultaneous recording of one channel ECG was also made. Epochs of 4 s and 1 min were selected from baseline, asphyxia and recovery (every 10 min) and their independent components and power spectra were calculated. The improvement in normalized power spectrum of EEG obtained for all animals was 7.71+/-3.63 db at the 3rd minute of recovery and dropped to 1.15+/-0.60 db at 63rd minute. The application of ICA has been particularly useful when the power of EEG is low, such as that observed during early brain hypoxic-asphyxic injury. The method is also useful in situations where accurate indications of EEG signal power and frequency content are needed.

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Year:  2001        PMID: 11459613     DOI: 10.1016/s0165-0270(01)00366-1

Source DB:  PubMed          Journal:  J Neurosci Methods        ISSN: 0165-0270            Impact factor:   2.390


  6 in total

1.  Simultaneously recorded EEG-fMRI: removal of gradient artifacts by subtraction of head movement related average artifact waveforms.

Authors:  Limin Sun; Hermann Hinrichs
Journal:  Hum Brain Mapp       Date:  2009-10       Impact factor: 5.038

2.  Statistical feature extraction for artifact removal from concurrent fMRI-EEG recordings.

Authors:  Zhongming Liu; Jacco A de Zwart; Peter van Gelderen; Li-Wei Kuo; Jeff H Duyn
Journal:  Neuroimage       Date:  2011-10-20       Impact factor: 6.556

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.  Robust detection of heartbeats using association models from blood pressure and EEG signals.

Authors:  Taegyun Jeon; Jongmin Yu; Witold Pedrycz; Moongu Jeon; Boreom Lee; Byeongcheol Lee
Journal:  Biomed Eng Online       Date:  2016-01-15       Impact factor: 2.819

5.  Clustering-Constrained ICA for Ballistocardiogram Artifacts Removal in Simultaneous EEG-fMRI.

Authors:  Kai Wang; Wenjie Li; Li Dong; Ling Zou; Changming Wang
Journal:  Front Neurosci       Date:  2018-02-13       Impact factor: 4.677

6.  Human emotion classification based on multiple physiological signals by wearable system.

Authors:  Xin Liu; Qisong Wang; Dan Liu; Yuan Wang; Yan Zhang; Ou Bai; Jinwei Sun
Journal:  Technol Health Care       Date:  2018       Impact factor: 1.285

  6 in total

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