Adaptable and Robust EEG Bad Channel Detection Using Local Outlier Factor (LOF)

Electroencephalogram (EEG) data are typically affected by artifacts. The detection and removal of bad channels (i.e., with poor signal-to-noise ratio) is a crucial initial step. EEG data acquired from different populations require different cleaning strategies due to the inherent differences in the...

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Detalles Bibliográficos
Autores principales: Kumaravel, Velu Prabhakar, Buiatti, Marco, Parise, Eugenio, Farella, Elisabetta
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9571252/
https://www.ncbi.nlm.nih.gov/pubmed/36236413
http://dx.doi.org/10.3390/s22197314

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9571252/
https://www.ncbi.nlm.nih.gov/pubmed/36236413
http://dx.doi.org/10.3390/s22197314

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