A Post-Recurrent Module added to RNNs yields 9% better P300 classification while identifying key spatio-temporal EEG patterns that match established neuroscience descriptions of the P300 wave.
Asurveyondeeplearning-basednon-invasivebrainsignals: recentadvancesandnewfrontiers
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The paper surveys technical requirements, use cases, challenges, and future trends for building brain-computer interfaces on top of 6G wireless networks.
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Explainability of Recurrent Neural Networks for Enhancing P300-based Brain-Computer Interfaces
A Post-Recurrent Module added to RNNs yields 9% better P300 classification while identifying key spatio-temporal EEG patterns that match established neuroscience descriptions of the P300 wave.
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Toward 6G-enabled Brain Computer Interfaces: Technical Requirements, Use Cases, Challenges, and Future Trends
The paper surveys technical requirements, use cases, challenges, and future trends for building brain-computer interfaces on top of 6G wireless networks.