Movement stability analysis of surface electromyography-based elbow power assistance

Area of Science:

• Robotics and Human-Machine Interaction
• Biomechanics and Motor Control
• Biomedical Engineering

Background:

• Surface electromyography (SEMG) signals are crucial for controlling power assistive devices.
• The inherent noise in SEMG signals can limit the effectiveness and naturalness of these assistive devices.
• Understanding the impact of assistive power levels on human movement stability is essential for device optimization.

Purpose of the Study:

• To investigate how variations in SEMG-based assistive power affect human movement stability.
• To quantify the relationship between the amount of SEMG-based assistive torque and movement stability metrics.
• To establish guidelines for optimizing SEMG-based assistive power for natural human movement.

Main Methods:

• A robotic device delivered torque proportional to SEMG-estimated torque for elbow flexion assistance.
• Twelve volunteers participated in experiments involving varying levels of assistive torque.
• Movement stability was quantified using the maximum finite-time Lyapunov exponent (MFTLE) and kinematic variability.

Main Results:

• Movement stability, as measured by MFTLE, decreased with increasing levels of assistive torque relative to human torque.
• Kinematic variability of elbow movements increased proportionally with the increase in assistive torque.
• Higher levels of SEMG-based assistive torque led to less stable and more variable movements.

Conclusions:

• SEMG-based assistive torque levels should be carefully managed to ensure natural and stable human movements.
• Maintaining SEMG-based assistive torque below the level of voluntary human torque is recommended for optimal assistance.
• This research provides a quantitative foundation for determining appropriate SEMG-based assistive power in rehabilitation and assistive technologies.