Data Augmentation: Using Channel-Level Recombination to Improve Classification Performance for Motor Imagery EEG

The quality and quantity of training data are crucial to the performance of a deep-learning-based brain-computer interface (BCI) system. However, it is not practical to record EEG data over several long calibration sessions. A promising time- and cost-efficient solution is artificial data generation...

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Detalles Bibliográficos
Autores principales: Pei, Yu, Luo, Zhiguo, Yan, Ye, Yan, Huijiong, Jiang, Jing, Li, Weiguo, Xie, Liang, Yin, Erwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Human Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7990774/
https://www.ncbi.nlm.nih.gov/pubmed/33776673
http://dx.doi.org/10.3389/fnhum.2021.645952

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7990774/
https://www.ncbi.nlm.nih.gov/pubmed/33776673
http://dx.doi.org/10.3389/fnhum.2021.645952

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