A Practical System for 3-D Hand Pose Tracking Using EMG Wearables With Applications to Prosthetics and User Interfaces

Keyphrases

• User Interface 100%
• Electromyography 100%
• Finger Movement 100%
• Electromyography Signal 66%
• Finger Tracking 66%
• Low Energy 33%
• Multiple Fingers 33%
• Healthcare 33%
• Smartphone 33%
• Natural Variation 33%
• Lower End 33%
• Complex Patterns 33%
• Haptics 33%
• Transfer Learning Algorithm 33%
• Recurrent Neural Network 33%
• Encoder-decoder 33%
• Processing Latency 33%
• Prosthetic Devices 33%
• Electrical Potential 33%
• Energy Overhead 33%
• Wrist Position 33%
• Training Approaches 33%
• Augmented Reality 33%
• New User 33%
• Mounting Position 33%
• Sensor Information 33%
• Anatomical Constraints 33%
• Motion Sensing 33%
• Motion Pattern 33%
• Sports Analytics 33%
• U-Net 33%
• Finger Joint Angle 33%
• Training Overhead 33%

Engineering

• Prosthetics 100%
• Angle Joint 50%
• Learning Algorithm 50%
• Haptics 50%
• Electrical Potential 50%
• Mounting Position 50%
• Augmented Reality 50%
• Natural Variation 50%
• Recurrent Neural Network 50%
• Transfer Learning 50%