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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...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2022
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| Materias: | |
| 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 |