A single-trial multi-class classification of various motor imagery tasks for EEG-based brain-computer interface communication

Keyphrases

• Motor Imagery Task 100%
• Brain-computer Interface 100%
• Multi-class Classification 100%
• Classification Accuracy 60%
• Visual Cortex 40%
• Motor Imagery 40%
• Cortex Activation 40%
• Mental Strategies 40%
• Class Classification 40%
• Brain Activity 20%
• Motor Cortex 20%
• T-test 20%
• Classification Results 20%
• Beta Rhythm 20%
• App Usability 20%
• Japanese Characters 20%
• Two-class Classification 20%
• Alpha Rhythm 20%
• Kanji 20%
• EEG Signals 20%
• BCI Applications 20%
• EEG Electrodes 20%

Computer Science

• Classification Accuracy 100%
• Computer Interface 100%
• Multiclass Classification 100%
• Multi Class Classification 100%
• Class Classification 100%
• Experimental Result 33%
• Brain Activity 33%
• Support Vector Machine 33%
• Healthy Subject 33%
• classification result 33%

Neuroscience

• Electroencephalography 100%
• Brain-Computer Interface 100%
• Visual Cortex 66%
• Alpha Wave 33%