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dc.contributor.authorBoudet, Samuelen_US
dc.contributor.authorPeyrodie, Laurenten_US
dc.contributor.authorSzurhaj, Williamen_US
dc.contributor.authorBolo, Nicolasen_US
dc.contributor.authorPinti, Antonioen_US
dc.contributor.authorGallois, Philippeen_US
dc.date.accessioned2014-11-03T17:40:47Z
dc.date.issued2014en_US
dc.identifier.citationBoudet, Samuel, Laurent Peyrodie, William Szurhaj, Nicolas Bolo, Antonio Pinti, and Philippe Gallois. 2014. “Dual Adaptive Filtering by Optimal Projection Applied to Filter Muscle Artifacts on EEG and Comparative Study.” The Scientific World Journal 2014 (1): 374679. doi:10.1155/2014/374679. http://dx.doi.org/10.1155/2014/374679.en
dc.identifier.issn2356-6140en
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:13347652
dc.description.abstractMuscle 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 while preserving true cerebral signals. DAFOP is a two-step method. The first step consists in applying the common spatial pattern (CSP) method to two frequency windows to identify the slowest components which will be considered as cerebral sources. The two frequency windows are defined by optimizing convolutional filters. The second step consists in using a regression method to reconstruct the signal independently within various frequency windows. This method was evaluated by two neurologists on a selection of 114 pages with muscle artifacts, from 20 clinical recordings of awake and sleeping adults, subject to pathological signals and epileptic seizures. A blind comparison was then conducted with the canonical correlation analysis (CCA) method and conventional low-pass filtering at 30 Hz. The filtering rate was 84.3% for muscle artifacts with a 6.4% reduction of cerebral signals even for the fastest waves. DAFOP was found to be significantly more efficient than CCA and 30 Hz filters. The DAFOP method is fast and automatic and can be easily used in clinical EEG recordings.en
dc.language.isoen_USen
dc.publisherHindawi Publishing Corporationen
dc.relation.isversionofdoi:10.1155/2014/374679en
dc.relation.hasversionhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC4178918/pdf/en
dash.licenseLAAen_US
dc.titleDual Adaptive Filtering by Optimal Projection Applied to Filter Muscle Artifacts on EEG and Comparative Studyen
dc.typeJournal Articleen_US
dc.description.versionVersion of Recorden
dc.relation.journalThe Scientific World Journalen
dash.depositing.authorBolo, Nicolasen_US
dc.date.available2014-11-03T17:40:47Z
dc.identifier.doi10.1155/2014/374679*
dash.contributor.affiliatedBolo, Nicolas


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