SEMG Based Wrist Movement Recognition with Portable Sensing Device

Computer Science

• Classification Accuracy 100%
• Linear Discriminant Analysis 100%
• Template Matching 100%
• Support Vector Machine 66%
• Electromyography 66%
• Experimental Result 33%
• classification result 33%
• Classification Task 33%
• Feature Extraction 33%
• Classification Performance 33%
• Recognition Accuracy 33%
• Acquisition Process 33%