Temporal and frequency feature extraction with canonical variates analysis for multi-class imagery task

@article{Zhang2008TemporalAF,
  title={Temporal and frequency feature extraction with canonical variates analysis for multi-class imagery task},
  author={Xiu Zhang and Xingyu Wang},
  journal={2008 Chinese Control and Decision Conference},
  year={2008},
  pages={2228-2232}
}
The objective of this study is to improve the accuracy of classification for a multi-imagery task by using canonical variates analysis in a brain-computer interface (BCI). Electroencephalogram (EEG) is recorded from subjects performing a four-class motor imaginary task, left hand, right hand, foot and tongue. Temporal features are extracted as squared band pass filtered EEG, and frequency features are extracted as energy in specific rhythms. Features in both domains are projected into a… CONTINUE READING