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Classification of Motor Imagery EEG Signals Based on Data Augmentation and Convolutional Neural Networks
In brain–computer interface (BCI) systems, motor imagery electroencephalography (MI-EEG) signals are commonly used to detect participant intent. Many factors, including low signal-to-noise ratios and few high-quality samples, make MI classification difficult. In order for BCI systems to function, MI...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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MDPI
2023
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9961359/ https://www.ncbi.nlm.nih.gov/pubmed/36850530 http://dx.doi.org/10.3390/s23041932 |