Mitigating Compensatory Movements in Prosthesis Users via Adaptive Collaborative Robotics.

Area of Science:

• Robotics
• Biomechanics
• Human-Computer Interaction

Background:

• Prosthetic devices restore partial limb function but rarely full mobility, leading to compensatory movements, discomfort, and physical strain.
• Existing solutions often fail to fully address the complex interplay between residual limb capabilities and task demands.

Purpose of the Study:

• To develop a novel human-robot collaboration framework to mitigate compensatory movements in prosthesis users.
• To enhance functional mobility and comfort by exploiting residual motion and respecting task requirements.

Main Methods:

• A personalized mobility model was created to quantify joint limitations and the cost of compensatory movements.
• A constrained optimization framework computed optimal user postures, guiding a collaborative robot to reconfigure the task environment.
• The framework was validated using a new body-powered prosthetic device for single-finger amputation.

Main Results:

• A robotic assistant, informed by the user-specific mobility model, outperformed human partners in handover tasks.
• Prosthesis user grasp efficiency was improved, and compensatory movements in functioning joints were reduced.
• Experiments with healthy subjects wearing the prosthesis demonstrated the framework's effectiveness.

Conclusions:

• The proposed human-robot collaboration framework effectively reduces compensatory movements in prosthesis users.
• Collaborative robots can serve as effective assistants in workplace and caregiving settings, promoting inclusion.
• This approach enhances the integration of prosthetic devices into daily activities, improving user quality of life.