Machine learning techniques for detecting motor imagery in upper limbs

Mathematics

• Classifier 23%
• Demand 21%
• Elections 28%
• Electroencephalogram (EEG) 28%
• Feature Extraction 95%
• Frequency Domain 44%
• Human-machine Interface 42%
• Imagery 94%
• Machine Learning 70%
• Model 7%
• Quality of Life 30%
• Random Forest 31%
• Strategy 30%
• Time Domain 22%

Business & Economics

• Classifier 25%
• Elections 21%
• Electroencephalogram (EEG) 24%
• Feature Extraction 100%
• Frequency Domain 54%
• Imagery 53%
• Machine Learning 84%
• Quality of Life 23%

Engineering & Materials Science

• Classifiers 15%
• Electroencephalography 20%
• Feature extraction 49%
• Machine learning 46%
• Random forests 22%