Selection of EMG Sensors Based on Motion Coordinated Analysis

Area of Science:

• Biomedical Engineering
• Neuroscience
• Rehabilitation Technology

Background:

• Intelligent prostheses offer solutions for disabled individuals' mobility.
• Optimal electromyography (EMG) sensor placement is crucial for enhancing prosthesis motion recognition.
• Understanding EMG spatial distribution and muscle connections is key to improving prosthesis control.

Purpose of the Study:

• To analyze EMG spatial distribution and muscle functional networks under different movement conditions.
• To identify critical muscle groups reflecting user movement intention for prosthesis control.
• To simplify EMG sensor distribution within prosthetic sockets.

Main Methods:

• Mutual information analysis to construct muscle functional networks.
• Node characteristic analysis and importance evaluation for network features.
• Convergent cross-mapping to create directed networks and determine critical muscle groups.

Main Results:

• The proposed method accurately determines optimal EMG sensor locations.
• Network characteristics effectively distinguish between different movement intentions.
• Simplified EMG sensor distribution enhances prosthesis usability.

Conclusions:

• This approach provides a new strategy for decoding the relationship between neural control and body movement.
• Optimized EMG sensor placement improves intelligent prosthesis performance.
• The findings contribute to more intuitive and effective prosthetic limb control.