Prediction of Inefficient BCI Users Based on Cognitive Skills and Personality Traits
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Publisher
Springer International Publishing
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https://link.springer.com/content/pdf/10.1007/978-3-030-92310-5_10
Reference24 articles.
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4. Jeunet, C., N’Kaoua, B., Subramanian, S., Hachet, M., Lotte, F.: Predicting mental imagery-based BCI performance from personality, cognitive profile and neurophysiological patterns. PLoS One 10(12), e0143962 (2015)
5. Khan, M.A., Das, R., Iversen, H.K., Puthusserypady, S.: Review on motor imagery based BCI systems for upper limb post-stroke neurorehabilitation: from designing to application. Comput. Biol. Med. 123, 103843 (2020)
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1. Large scale investigation of the effect of gender on mu rhythm suppression in motor imagery brain-computer interfaces;Brain-Computer Interfaces;2024-05-04
2. Classification of motor imagery EEG using deep learning increases performance in inefficient BCI users;PLOS ONE;2022-07-22
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