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The potential of convolutional neural networks for identifying neural states based on electrophysiological signals: experiments on synthetic and real patient data
Processing incoming neural oscillatory signals in real-time and decoding from them relevant behavioral or pathological states is often required for adaptive Deep Brain Stimulation (aDBS) and other brain-computer interface (BCI) applications. Most current approaches rely on first extracting a set of...
Autores principales: | Rodriguez, Fernando, He, Shenghong, Tan, Huiling |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10272439/ https://www.ncbi.nlm.nih.gov/pubmed/37333834 http://dx.doi.org/10.3389/fnhum.2023.1134599 |
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