Prediction of Individual User’s Dynamic Ranges of EEG Features from Resting-State EEG Data for Evaluating Their Suitability for Passive Brain–Computer Interface Applications

With the recent development of low-cost wearable electroencephalogram (EEG) recording systems, passive brain–computer interface (pBCI) applications are being actively studied for a variety of application areas, such as education, entertainment, and healthcare. Various EEG features have been employed...

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Detalles Bibliográficos
Autores principales: Cha, Ho-Seung, Han, Chang-Hee, Im, Chang-Hwan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7071472/
https://www.ncbi.nlm.nih.gov/pubmed/32059543
http://dx.doi.org/10.3390/s20040988

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7071472/
https://www.ncbi.nlm.nih.gov/pubmed/32059543
http://dx.doi.org/10.3390/s20040988

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