Unsupervised Event Characterization and Detection in Multichannel Signals: An EEG application

In this paper, we propose a new unsupervised method to automatically characterize and detect events in multichannel signals. This method is used to identify artifacts in electroencephalogram (EEG) recordings of brain activity. The proposed algorithm has been evaluated and compared with a supervised...

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Detalles Bibliográficos
Autores principales: Mur, Angel, Dormido, Raquel, Vega, Jesús, Duro, Natividad, Dormido-Canto, Sebastian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4851103/
https://www.ncbi.nlm.nih.gov/pubmed/27120605
http://dx.doi.org/10.3390/s16040590

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4851103/
https://www.ncbi.nlm.nih.gov/pubmed/27120605
http://dx.doi.org/10.3390/s16040590

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