Improvements of Adaptive Filtering by Optimal Projection to filter different artifact types on long duration EEG recordingsReport as inadecuate

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1 UTSB - Unité de traitement des signaux Biomédicaux 2 LAGIS-SI LAGIS - Laboratoire d-Automatique, Génie Informatique et Signal 3 I3MTO - Imagerie Multimodale Multiéchelle et Modélisation du Tissu Osseux et articulaire

Abstract : Adaptive Filtering by Optimal Projection AFOP is an automatic method for reducing ocular and muscular artifacts on electro-encephalographic EEG recordings. This paper presents two additions to this method: an improvement of the stability of ocular artifact filtering and an adaptation of the method for filtering electrode artifacts. With these improvements, it is possible to reduce almost all the current types of artifacts, while preserving brain signals, particularly those characterising epilepsy. This generalised method consists of dividing the signal into several time-frequency windows, and in applying different spatial filters to each. Two steps are required to define one of these spatial filters: the first step consists of defining artifact spatial projection using the Common Spatial Pattern CSP method and the second consists of defining EEG spatial projection via regression. For this second step, a progressive orthogonalisation process is proposed to improve stability. This method has been tested on long-duration EEG recordings of epileptic patients. A neurologist quantified the ratio of removed artifacts and the ratio of preserved EEG. Among the 330 artifacted pages used for evaluation, readability was judged better for 78% of pages, equal for 20% of pages, and worse for 2%. Artifact amplitudes were reduced by 80% on average. At the same time, brain sources were preserved in amplitude from 70% to 95% depending on the type of waves alpha, theta, delta, spikes, etc

A blind comparison with manual Independent Component Analysis ICA was also realised. The results show that this method is competitive and useful for routine clinical practice.

Keywords : ICA AFOP-DAFOP artifact rejection EEG

Author: Samuel Boudet - Laurent Peyrodie - Gérard Forzy - Antonio Pinti - Hechmi Toumi - Philippe Gallois -



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