Impact of dataset size and long-term ECoG-based BCI usage on deep learning decoders performance

Impact of dataset size and long-term ECoG-based BCI usage on deep learning decoders performance

IntroductionIn brain-computer interfaces (BCI) research, recording data is time-consuming and expensive, which limits access to big datasets. This may influence the BCI system performance as machine learning methods depend strongly on the training dataset size. Important questions arise: taking into...

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Bibliographic Details
Main Authors: Maciej Śliwowski, Matthieu Martin, Antoine Souloumiac, Pierre Blanchart, Tetiana Aksenova
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-03-01
Series:Frontiers in Human Neuroscience
Subjects:
ECoG
motor imagery
deep learning
tetraplegia
adaptation
dataset size
Online Access:https://www.frontiersin.org/articles/10.3389/fnhum.2023.1111645/full

Internet

https://www.frontiersin.org/articles/10.3389/fnhum.2023.1111645/full

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