Motor Imagery EEG Classification Based on CEEMDAN-CWT Characterization
Abstract
References
Index Terms
- Motor Imagery EEG Classification Based on CEEMDAN-CWT Characterization
Recommendations
Multifeature Analysis in Motor Imagery EEG Classification
ISECS '10: Proceedings of the 2010 Third International Symposium on Electronic Commerce and SecurityClassification of EEG signals is core issues on EEG-based brain-computer interface (BCI). Typically, such classification has been performed using features extracted from EEG signals. Many features have proved to be unique enough to used in BCI ...
Modified CC-LR algorithm with three diverse feature sets for motor imagery tasks classification in EEG based brain-computer interface
Motor imagery (MI) tasks classification provides an important basis for designing brain-computer interface (BCI) systems. If the MI tasks are reliably distinguished through identifying typical patterns in electroencephalography (EEG) data, a motor ...
A hybrid ensemble voting-based residual attention network for motor imagery EEG Classification
AbstractMulti-class motor imagery Electroencephalography (EEG) activity decoding has always been challenging for the development of Brain Computer Interface (BCI) system. Deep learning has recently emerged as a powerful approach for BCI system development ...
Comments
Information & Contributors
Information
Published In

Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed limited
Funding Sources
Conference
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 21Total Downloads
- Downloads (Last 12 months)21
- Downloads (Last 6 weeks)5
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format