Artifact removal from EEG signals recorded in non-restricted environmentArtifact removal from EEG signals recorded in non-restricted environment

• Autorzy: Jamil Zainab , Jamil Afshan , Majid Muhammad

Identyfikatory

DOI

10.1016/j.bbe.2021.03.009

• Języki publikacji: EN

Abstrakty

EN

Electroencephalography (EEG) signals are always accompanied by endogenous and exogenous artifacts. Research carried out in the past few years focused on EEG artifact removal considered EEG signals recorded in a restricted lab environment. Considering the importance of EEG in daily life activities, no definitive approach is presented in removing blink artifacts from non-restricted EEG recordings. In this paper, a new supervised artifact removal method is proposed that classifies EEG chunks having eye movements and then utilizes independent component analysis and discrete wavelet transform to eliminate the ocular artifacts. The EEG data is acquired from 29 subjects in a non-restricted environment where the subject has to watch videos while walking and giving gestures and facial expressions. Thirteen morphological features are extracted from the recorded EEG signals to classify chunks with eye movements. The EEG chunks with eye movements are further processed to remove noise without distorting the morphology of signals. The proposed method is tested for eye movements and shows an improved performance in terms of correlation, mutual information, phase difference, and computational time over unsupervised modified multi-scale sample entropy and kurtosis, and wavelet enhanced independent component analysis based approaches. Moreover, the computed values of statistical parameters including sensitivity and specificity show the robustness of the proposed scheme.

Słowa kluczowe

EN

electroencephalography; EEG; ocular artifacts; feature extraction; feature classification; independent component analysis; discrete wavelet transform

PL

elektroencefalografia; EEG; ekstrakcja cech; analiza składowych niezależnych; dyskretna transformata falkowa

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2021
• Tom: Vol. 41, no. 2
• Strony: 503--515
• Opis fizyczny: Bibliogr. 38 poz., rys., tab., wykr.

Twórcy

autor

Jamil Zainab

• Department of Computer Engineering, University of Engineering and Technology Taxila, Pakistan

autor

Jamil Afshan

• Department of Computer Engineering, University of Engineering and Technology Taxila, Pakistan

autor

Majid Muhammad

• Department of Computer Engineering, University of Engineering and Technology Taxila, Pakistan

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).