Improving robustness against electrode shift of sEMG based hand gesture recognition using online semi-supervised learning

INIS

• electrodes 100%
• learning 80%
• hands 80%
• algorithms 60%
• accuracy 40%
• surfaces 40%
• devices 40%
• data 20%
• comparative evaluations 20%
• gases 20%
• classification 20%
• signals 20%

Computer Science

• Gesture Recognition 80%
• Semi-Supervised Learning 80%
• Electromyography 40%
• Learning Algorithm 40%
• Recognition System 20%
• Algorithms 20%
• Classification Accuracy 20%
• Classification (Machine Learning) 20%
• Online Algorithm 20%
• Unlabeled Sample 20%
• Channels 20%
• Accuracy 20%
• User 20%
• Identification 20%