Title
Multimodal Fuzzy Fusion for Enhancing the Motor-Imagery-Based Brain Computer Interface.
Abstract
Brain-computer interface technologies, such as steady-state visually evoked potential, P300, and motor imagery are methods of communication between the human brain and the external devices. Motor imagery-based brain-computer interfaces are popular because they avoid unnecessary external stimuli. Although feature extraction methods have been illustrated in several machine intelligent systems in mot...
Year
DOI
Venue
2019
10.1109/MCI.2018.2881647
IEEE Computational Intelligence Magazine
Keywords
Field
DocType
Electroencephalography,Feature extraction,Brain-computer interfaces,Performance evaluation,Data acquisition,Standards,Transforms
Pattern recognition,Intelligent decision support system,Computer science,Data acquisition,Fuzzy logic,Brain–computer interface,Feature extraction,Artificial intelligence,Fuzzy fusion,Electroencephalography,Machine learning,Motor imagery
Journal
Volume
Issue
ISSN
14
1
1556-603X
Citations 
PageRank 
References 
5
0.38
0
Authors
10
Name
Order
Citations
PageRank
Li-Wei Ko151958.70
Yi-Chen Lu250.38
Humberto Bustince31938134.10
yucheng chang481.73
Yang Chang550.38
Javier Fernandez678246.37
Yu-Kai Wang77416.92
José Antonio Sanz842923.40
Graçaliz Pereira Dimuro966743.93
Chin-Teng Lin103840392.55