An Efficient Framework for EEG Analysis with Application to Hybrid Brain Computer Interfaces Based on Motor Imagery and P300
The hybrid brain computer interface (BCI) based on motor imagery (MI) and P300 has been a preferred strategy aiming to improve the detection performance through combining the features of each. However, current methods used for combining these two modalities optimize them separately, which does not r...
Main Authors: | Jinyi Long, Jue Wang, Tianyou Yu |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2017-01-01
|
Series: | Computational Intelligence and Neuroscience |
Online Access: | http://dx.doi.org/10.1155/2017/9528097 |
Similar Items
-
Adaptive Brain-computer Interface Using Motor-imagery EEG
by: Shih-Wei Lu, et al.
Published: (2007) -
Multi-class motor imagery EEG decoding for brain-computer interfaces
by: Deng eWang, et al.
Published: (2012-10-01) -
A Hybrid Brain-Computer Interface-Based Mail Client
by: Tianyou Yu, et al.
Published: (2013-01-01) -
EEG-Based Brain-Computer Interfaces Using Motor-Imagery: Techniques and Challenges
by: Natasha Padfield, et al.
Published: (2019-03-01) -
Advanced TSGL-EEGNet for Motor Imagery EEG-Based Brain-Computer Interfaces
by: Xin Deng, et al.
Published: (2021-01-01)