Subject-specific time-frequency selection for multi-class motor imagery-based BCIs using few Laplacian EEG channels

Keyphrases

• Laplacian 100%
• Subject-specific 100%
• Brain-computer Interface 100%
• Electroencephalogram 100%
• Multi-class Motor Imagery 100%
• Time-frequency Diversity 100%
• Motor Imagery 75%
• Multi-class Classification 50%
• Optimal Frequency Band 50%
• Classification Performance 25%
• Electroencephalography 25%
• Training Data 25%
• Small Standard Deviation 25%
• Classification Results 25%
• Multi-class 25%
• Sensorimotor Area 25%
• Arts-based Methods 25%
• Fisher Discriminant Analysis 25%
• Motor Intention 25%

Computer Science

• Multiclass Classification 100%
• Laplace Operator 100%
• Multi Class Classification 100%
• Classification Performance 50%
• Training Dataset 50%
• classification result 50%
• Discriminant Analysis 50%
• Related Feature 50%
• Interface Dataset 50%

Engineering

• Laplace Operator 100%
• Brain-Computer Interface 100%
• Motor Imagery 100%
• Optimal Frequency 50%
• Multiclass Classification 50%
• State-of-the-Art Method 25%
• Classification Performance 25%
• Analysis Type 25%