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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...
Autores principales: | Ma, Teng, Li, Fali, Li, Peiyang, Yao, Dezhong, Zhang, Yangsong, Xu, Peng |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2018
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Materias: | |
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 |
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