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dc.contributor.authorCinar S.
dc.contributor.authorAcir N.
dc.description2016 Medical Technologies National Conference, TIPTEKNO 2016 -- 27 October 2016 through 29 October 2016 -- -- 126633en_US
dc.description.abstractEye movements (saccade, blink and etc.) cause artefacts in Electroencephalogram recordings. The ocular artefact can distort the EEG signals. Removal of ocular artefact is important issue in EEG signal analysis. The main task of artefact removal algorithms is to obtain cleaned EEG without losing meaningful EEG signal. The main focus of this work is to remove ocular artefact automatically by using Independent Component Analysis and Chauvenet criterion. The method is tested on real dataset. Relative error and Correlation coefficient are used for the performance test. The performance of the proposed method was Relative error= 0.273±0.148, Correlation coefficients 0.943± 0.042 in the dataset. The results show that the porposed method effectively removes ocular artefacts in EEG. © 2016 IEEE.en_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.subjectChauvenet criterionen_US
dc.subjectremoval of arefactsen_US
dc.titleAutomatic removal of ocular artefacts in EEG signal by using independent component analysis and Chauvenet criterion [Baglmslz bileşen analizi ve chauvenet kriteri kullanarak EEG sinyallerindeki oktiler artefaktlan otomatik yok etme]en_US
dc.relation.journal2016 Medical Technologies National Conference, TIPTEKNO 2016en_US
dc.departmentNiğde ÖHÜen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US

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