Optimal EEG channels selection for alcoholism screening using EMD domain statistical features and harmony search algorithm

• Autorzy: Bavkar Sandeep , Iyer Brijesh , Deosarkar Shankar

Identyfikatory

DOI

10.1016/j.bbe.2020.11.001

• Języki publikacji: EN

Abstrakty

EN

Alcoholism can be analyzed by Electroencephalogram (EEG) data. Finding an optimal subset of EEG channels for alcoholism detection is a challenging task. The paper reports a new methodology for the detection of optimal channels for alcoholism analysis using EEG data. The proposed technique employs the Empirical Mode Decomposition (EMD) technique to extract the amplitude and frequency modulated bandwidth features from the Intrinsic Mode Function (IMF) and ensemble subspace K-NN as a classifier to classify alcoholics and normal. The optimum channels are selected, using a harmony search algorithm. The fitness value of discrete binary harmony search (DBHS) optimization algorithms is calculated using accuracy and sensitivity achieved by the ensemble subspace K-Nearest Neighbor classifier. Experimental outcomes indicate that the optimal channel selected by the harmony search algorithm has biological inference related to the alcoholic subject. The proposed approach reports a classification accuracy of 93.87%, with only 12 detected EEG channels.

Słowa kluczowe

EN

alcoholism; EEG; electroencephalogram; ensemble subspace K NN; EMD; empirical mode decomposition; harmony search

PL

alkoholizm; EEG; elektroencefalogram; EMD; empiryczna dekompozycja sygnału

• 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. 1
• Strony: 83--96
• Opis fizyczny: Bibliogr. 44 poz., rys., tab., wykr.

Twórcy

autor

Bavkar Sandeep

• Department of Electronics & Telecommunication Engineering Dr.Babasaheb Ambedkar Technological University, Lonere 402103, India

autor

Iyer Brijesh

• Department of Electronics & Telecommunication Engineering Dr. Babasaheb Ambedkar Technological University, Lonere 402103, India

autor

Deosarkar Shankar

• Department of Electronics & Telecommunication Engineering Dr.Babasaheb Ambedkar Technological University, Lonere 402103, India

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).