Comparative analysis of spectral approaches to feature extraction for EEG-based motor imagery classification.

Computer Science

• Computer Interface 100%
• Comparative Analysis 100%
• Feature Extraction 100%
• Power Spectral Density 100%
• Classification Accuracy 50%
• Data Analysis 50%
• Clinical Application 50%
• Representing Set 50%
• Spectral Content 50%
• Scientific Application 50%
• Signal Representation 50%
• Energy Distribution 50%

Engineering

• Feature Extraction 100%
• Motor Imagery 100%
• Comparative Analysis 100%
• Brain-Computer Interface 50%
• Power Spectral Density 50%
• Separability 25%
• Oscillatory 25%
• Classification Accuracy 25%
• Energy Distribution 25%
• Signal Representation 25%

Neuroscience

• Electroencephalogram 100%
• Brain-Computer Interface 66%