Authors: Chinmayee Dora; Pradyut Kumar Biswal
Addresses: Department of Electronics and Telecommunication, International Institute of Information Technology, Bhubaneswar, Odissa, India ' Department of Electronics and Telecommunication, International Institute of Information Technology, Bhubaneswar, Odissa, India
Abstract: Electroencephalograms (EEGs) signal, obtained by recording the brain waves are used to analyse health problems related to neurology and clinical neurophysiology. This signal is often contaminated by a range of physiological and non-physiological artefacts, which leads to a misinterpretation in EEG signal analysis. Hence, artefact removal is one of the pre-processing step required for clinical usefulness of the EEG signal. One of the physiological artefact, i.e., electrocardiogram (ECG) contaminated EEG can affect the clinical analysis and diagnosis of brain health in various ways. This paper presents a review of engineering approaches adopted till date for ECG artefact identification and removal from contaminated EEG signal. In addition, the technical approach, computational extensiveness, input requirement and the results achieved with every method is discussed. Along with that, the feasibility study for real time implementation of the algorithms is discussed. Also, an analysis of these methods has been reported based on their performance.
Keywords: electroencephalogram; EEG; electrocardiogram; ECG; artefacts; independent component analysis; ICA; wavelet; source decomposition; adaptive noise cancellation; ANC; autoregression; adaptive neuro fuzzy inference system; ANFIS; support vector machine; SVM.
International Journal of Biomedical Engineering and Technology, 2020 Vol.32 No.4, pp.351 - 383
Received: 19 Apr 2017
Accepted: 21 Jul 2017
Published online: 05 May 2020 *