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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(More)
Expanded Disability Status Scale (EDSS) is the most widely used clinical scale to evaluate levels of multiple sclerosis (MS). As MS can lead to disruptions in the regulation of balance and the disability can be evaluated by force platform posturography, we have developed in this study a new strategy to estimate EDSS from posturographic data. 118 volunteers(More)
OBJECTIVE Further developments in EEG monitoring necessitate new methods of filtering to eliminate artifacts, without transforming relevant signals. This article presents an automatic filtering of EEG recordings, based on a spatio-temporal method called Adaptive Filtering by Optimal Projection or Dual Adaptive Filtering by Optimal Projection. Evaluation of(More)
Muscle artifacts constitute one of the major problems in electroencephalogram (EEG) examinations, particularly for the diagnosis of epilepsy, where pathological rhythms occur within the same frequency bands as those of artifacts. This paper proposes to use the method dual adaptive filtering by optimal projection (DAFOP) to automatically remove artifacts(More)
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