Classification of Five Control/Non-control States to Enhance Asynchronous Brain-Computer Interfaces

Discriminating EEG signals between control and non-control states is a key problem in asynchronous brain-computer interfaces, and recent studies have shown that fusion-based methods can significantly improve the classification accuracy of EEG signals. In this paper, we propose a Dempster-Shafer theo...

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Bibliographic Details

Published in:	WRC Symposium on Advanced Robotics and Automation (Online) pp. 51 - 54
Main Authors:	Liu, Xueshuo, Zhang, Qian, Li, Jiaxin, Wang, Hantao, Zhao, Jing
Format:	Conference Proceeding
Language:	English
Published:	IEEE 23.08.2024
Subjects:	Accuracy Brain-computer interfaces Complex networks Decision making Electroencephalography Feature extraction Optimization methods
ISSN:	2835-3358
Online Access:	Get full text
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