Impact of feature selection on sEMG signal classification

Keyphrases

• Feature Selection 100%
• Surface Electromyography (sEMG) 100%
• Signal Classification 100%
• Selection Strategy 20%
• Computational Cost 20%
• Computational Burden 20%
• Decision Tree 20%
• Computation Time 20%
• Support Vector Machine 20%
• Time Use 20%
• Precision-recall 20%
• Training Time 20%
• Nave Bayes 20%
• Impact Analysis 20%
• F1 Score 20%
• Testing Rates 20%
• Precision Accuracy 20%
• Four-channel 20%
• Irrelevant Features 20%
• Acquisition Device 20%
• K-nearest 20%
• Hand Gesture Classification 20%
• Hardware Development 20%
• Subject Selection 20%
• Classification Basis 20%
• Tree Support 20%
• Variance-based 20%

Computer Science

• Feature Selection 100%
• Feature Extraction 100%
• Electromyography 100%
• Analysis of Variance 40%
• Average Accuracy 20%
• Support Vector Machine 20%
• Impact Analysis 20%
• Nave Bayes 20%
• Selection Method 20%
• Time Consumption 20%
• Reduce Complexity 20%
• Decision Tree 20%