Recognition of motor imagery electroencephalography using independent component analysis and machine classifiers

Keyphrases

• International Cooperative Ataxia Rating Scale (ICARS) 100%
• MI-EEG 100%
• Machine Learning Classifiers 100%
• Support Vector Machine 33%
• Brain-computer Interface 33%
• Electroencephalography 33%
• Input Signals 33%
• Mental Simulation 33%
• Brain-computer Interface Systems 33%
• Back-propagation Artificial Neural Network (BP-ANN) 33%
• Area under the Receiver Operating Characteristic Curve 33%
• Radial Basis Function Neural Network (RBFNN) 33%
• Recognition Rate 33%
• Brain Signals 33%
• Misclassification Cost 33%
• Quality Classification 33%
• Lifting Task 33%
• Neural Input 33%
• Fisher Linear Discriminant 33%
• Cortical Potential 33%
• Neural Features 33%

Engineering

• Independent Component Analysis 100%
• Motor Imagery 100%
• Brain-Computer Interface 66%
• Misclassification 33%
• Input Signal 33%
• Recognition Rate 33%
• Receiver Operating Characteristic 33%
• Operating-Characteristic Curve 33%
• Fisher Linear Discriminant 33%
• Brain Signal 33%
• Neural Input 33%
• Support Vector Machine 33%
• Radial Basis Function Network 33%

Neuroscience

• Independent Component Analysis 100%
• Neural Network 66%
• Brain-Computer Interface 66%
• Support Vector Machine 33%
• Biomechanics 33%