Utilization of independent component analysis for accurate pathological ripple detection in intracranial EEG recordings recorded extra- and intra-operatively

OBJECTIVE: To develop and validate a detector that identifies ripple (80–200 Hz) events in intracranial EEG (iEEG) recordings in a referential montage and utilizes independent component analysis (ICA) to eliminate or reduce high-frequency artifact contamination. Also, investigate the correspondence...

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Détails bibliographiques
Publié dans:Clin Neurophysiol
Auteurs principaux: Shimamoto, Shoichi, Waldman, Zachary J., Orosz, Iren, Song, Inkyung, Bragin, Anatol, Fried, Itzhak, Engel, Jerome, Staba, Richard, Sharan, Ashwini, Wu, Chengyuan, Sperling, Michael R., Weiss, Shennan A.
Format: Artigo
Langue:Inglês
Publié: 2017
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Article
Accès en ligne:https://ncbi.nlm.nih.gov/pmc/articles/PMC5912211/
https://ncbi.nlm.nih.gov/pubmed/29113719
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.clinph.2017.08.036
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