Dependence of Brain–Computer Interface Control Training on Personality Traits
Author:
Publisher
Pleiades Publishing Ltd
Subject
General Chemistry,Biochemistry,General Medicine,Biophysics
Link
https://link.springer.com/content/pdf/10.1134/S1607672922060035.pdf
Reference18 articles.
1. Jeunet, C., N’Kaoua, B., Subramanian, S., et al., Predicting mental imagery-based bci performance from personality, cognitive profile and neurophysiological patterns, PLoS One, 2015, vol. 10, no. 12, p. e0143962.
2. Hammer, E.M., Kaufmann, T., Kleih, S.C., et al., Visuo-motor coordination ability predicts performance with brain-computer interfaces controlled by modulation of sensorimotor rhythms (SMR), Front. Hum. Neurosci., 2014, vol. 8, p. 574.
3. Vuckovic, A. and Osuagwu, B.A., Using a motor imagery questionnaire to estimate the performance of a brain-computer interface based on object-oriented motor imagery, Clin. Neurophysiol., 2013, vol. 124, no. 8, pp. 1586–1595.
4. Kubler, A., Nijboer, F., Mellinger, J., et al., Patients with ALS can use sensorimotor rhythms to operate a brain-computer interface, Neurology, 2005, vol. 64, no. 10, pp. 1775–1777.
5. Hagedorn, L.J., Leeuwis, N., and Alimardani, M., Prediction of inefficient BCI users based on cognitive skills and personality traits, bioRxiv, 2021, p. 461955.
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
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