Automatic removal ofocular artifacts from EEG data using adaptive filtering and independent component analysis

Carlos Guerrero-Mosquera, Angel Navia Vazquez

Research output: Indexed journal article Conference articlepeer-review

35 Citations (Scopus)

Abstract

A method to eliminate eye movement artifacts based on Independent Component Analysis (ICA) and Recursive Least Squares (RLS) is presented. The proposed algorithm combines the effective ICA capacity of separating artifacts from brain waves, together with the online interference cancellation achieved by adaptive filtering. The method uses separate electrodes localized close to the eyes (Fp1, Fp2, F7 and F8), that register vertical and horizontal eye movements, to extract a reference signal. Each reference input is first projected into ICA domain and then the interference is estimated using the RLS algorithm. This interference estimation is subtracted from the EEG components in the ICA domain. Results from experimental data demonstrate that this approach is suitable for eliminating artifacts caused by eye movements, and the principles of this method can be extended to certain other sources of artifacts as well. The method is easy to implement, stable, and presents a low computational cost.

Original languageEnglish
Pages (from-to)2317-2321
Number of pages5
JournalEuropean Signal Processing Conference
Publication statusPublished - 2009
Externally publishedYes
Event17th European Signal Processing Conference, EUSIPCO 2009 - Glasgow, United Kingdom
Duration: 24 Aug 200928 Aug 2009

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