共 50 条
- [1] Improving motor imagery BCI with user response to feedback [J]. Brain-Computer Interfaces, 2017, 4 (1-2): : 74 - 86
- [3] The Use of fMRI for the Evaluation of the Effect of Training in Motor Imagery BCI Users [J]. 2013 6TH INTERNATIONAL IEEE/EMBS CONFERENCE ON NEURAL ENGINEERING (NER), 2013, : 686 - 690
- [5] EEG motor imagery classification using deep learning approaches in naive BCI users [J]. BIOMEDICAL PHYSICS & ENGINEERING EXPRESS, 2023, 9 (04):
- [6] High Aptitude Motor-Imagery BCI Users Have Better Visuospatial Memory [J]. 2020 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), 2020, : 1518 - 1523
- [7] Profiling BCI users based on contralateral activity to improve kinesthetic motor imagery detection [J]. 2017 8TH INTERNATIONAL IEEE/EMBS CONFERENCE ON NEURAL ENGINEERING (NER), 2017, : 436 - 439
- [8] A Voting Optimized Strategy Based on ELM for Improving Classification of Motor Imagery BCI Data [J]. Cognitive Computation, 2014, 6 : 477 - 483
- [9] Classification of motor imagery EEG using deep learning increases performance in inefficient BCI users [J]. PLOS ONE, 2022, 17 (07):
- [10] Assessing The Relevance Of Neurophysiological Patterns To Predict Motor Imagery-based BCI Users' Performance [J]. 2020 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), 2020, : 2490 - 2495