Reducing Squat Physical Effort Using Personalized Assistance From an Ankle Exoskeleton.

Area of Science:

• Biomechanics
• Robotics
• Human-Computer Interaction

Background:

• Squatting is a physically demanding activity with high injury risk.
• Exoskeletons offer potential for reducing physical demands during squatting.
• Personalized assistance strategies for squatting exoskeletons remain underexplored.

Purpose of the Study:

• To investigate the efficacy of personalized assistance from a unilateral ankle exoskeleton in reducing physical effort during squatting.
• To develop and validate a human-in-the-loop Bayesian optimization scheme for personalized exoskeleton assistance.

Main Methods:

• A unilateral ankle exoskeleton was employed.
• A human-in-the-loop Bayesian optimization scheme was developed to minimize metabolic cost during squatting.
• Subject-specific assistance parameters were identified for ascending and descending phases of the squat.

Main Results:

• The personalized assistance condition reduced metabolic cost by 19.9% and rectus femoris muscle activity by 28.7% compared to unassisted squatting.
• The optimization process converged in an average of 15.8 minutes.
• Personalized assistance demonstrated a higher probability of improvement and greater metabolic cost reduction than a generic assistance condition.

Conclusions:

• Personalized ankle exoskeleton assistance is effective in minimizing physical effort during squatting.
• The developed optimization scheme provides subject-specific parameters for enhanced exoskeleton performance.
• This approach holds promise for reducing physical exertion in activities like squatting, with potential future applications in fatigue and injury risk mitigation.