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Performance Comparison Of State Of The Art Algorithms For Eog Artefacts Removal From Eeg Signals
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PERFORMANCE COMPARISON OF STATE – OF – THE – ART
ALGORITHMS FOR EOG ARTEFACTS REMOVAL FROM EEG SIGNALS
Nguyen Thi Huong
Course : QH-2007-I/CQ-D,Electronics and Telecommunications Technology
Major: Communication systems
Abstract:Electrooculogram (EOG) artefact in Electroencephalogram (EEG) can cause
difficulty in reading neural activity, such as epileptic spikes. Signal processing methods for
EOG artefact removal include: adaptive filtering with referenced EOG signal, and blind
separation without a reference signal.
The thesis compare state – of – the – art algorithms of these two methods using both simulted
and real data.
RRMSE (Relative Root Mean Squared Error) and the power ratio of artefact to signal are used
as performance measures in the comparison.
Keywords: EEG, EOG, artifact removal, adaptive filtering, blind separation.