An Adaptive Calibration Framework for mVEP-Based Brain-Computer Interface

Electroencephalogram signals and the states of subjects are nonstationary. To track changing states effectively, an adaptive calibration framework is proposed for the brain-computer interface (BCI) with the motion-onset visual evoked potential (mVEP) as the control signal. The core of this framework...

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Detalles Bibliográficos
Autores principales: Ma, Teng, Li, Fali, Li, Peiyang, Yao, Dezhong, Zhang, Yangsong, Xu, Peng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2018
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5846352/
https://www.ncbi.nlm.nih.gov/pubmed/29682000
http://dx.doi.org/10.1155/2018/9476432

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5846352/
https://www.ncbi.nlm.nih.gov/pubmed/29682000
http://dx.doi.org/10.1155/2018/9476432

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