Using the detectability index to predict P300 speller performance

Author:

Mainsah B O,Collins L M,Throckmorton C S

Funder

National Institutes of Health

Publisher

IOP Publishing

Subject

Cellular and Molecular Neuroscience,Biomedical Engineering

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Language Model-Guided Classifier Adaptation for Brain-Computer Interfaces for Communication;2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC);2022-10-09

2. Mitigating the Impact of Psychophysical Effects During Adaptive Stimulus Selection in the P300 Speller Brain-Computer Interface;2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC);2021-11-01

3. Subject-Independent ERP-Based Brain–Computer Interfaces;IEEE Transactions on Neural Systems and Rehabilitation Engineering;2018-04

4. Subject-Independent P300 BCI Using Ensemble Classifier, Dynamic Stopping and Adaptive Learning;GLOBECOM 2017 - 2017 IEEE Global Communications Conference;2017-12

5. A new multivariate empirical mode decomposition method for improving the performance of SSVEP-based brain–computer interface;Journal of Neural Engineering;2017-06-21

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