Automatic removal of ocular artefacts in EEG signal by using independent component analysis and Chauvenet criterion
Küçük Resim Yok
Tarih
2017
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
Özet
Eye 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.
Açıklama
2016 Medical Technologies National Conference, TIPTEKNO 2016 -- 2016-10-27 through 2016-10-29 -- Antalya -- 126633
Anahtar Kelimeler
Chauvenet criterion, ICA, removal of arefacts
Kaynak
2016 Medical Technologies National Conference, TIPTEKNO 2016
WoS Q Değeri
Scopus Q Değeri
N/A
