Lstmとnarxを用いた筋電位による指・手首の屈曲・伸展のモデル化

Key Points

• The research aims to model finger and wrist flexion and extension movements using EMG data.
• Utilized LSTM for motion identification
• Employed NARX for estimating joint angles
• Constructed a movement model based on deep learning techniques
• Conducted experiments for five specific movements
• Achieved high accuracy in identifying movements
• Successfully predicted finger and wrist flexion and extension
• Validated model performance for neutral wrist position