EEG Channel Selection Based on Neuron Proportion with SNN for Motor Imagery Classification

Computer Science

• Classification Accuracy 100%
• Neural Network 100%
• Computer Interface 100%
• Energy Consumption 66%
• Classification Process 66%
• Processing Speed 33%
• Neural Network Architecture 33%
• Computing Power 33%
• Low Power Consumption 33%
• Spatial Information 33%
• Temporal Information 33%
• Channel Signal 33%
• Spatiotemporal Data 33%
• Interface System 33%
• Application Performance 33%
• Classification Learning 33%
• Brain Structure 33%

Engineering

• Brain Structure 33%