Mitigating Compensatory Movements in Prosthesis Users via Adaptive Collaborative Robotics

TL;DR

This paper presents a human-robot collaboration framework that personalizes assistance to reduce compensatory movements in prosthesis users, improving task efficiency and comfort through an adaptive, optimized interaction model.

Contribution

It introduces a novel mobility model and constrained optimization approach that guides robots to reconfigure environments, enhancing prosthesis functionality and reducing physical strain.

Findings

Robotic assistance outperformed human partners in grasp tasks.

The framework reduced compensatory joint movements.

Enhanced prosthesis integration into daily activities.

Abstract

Prosthesis users can regain partial limb functionality, however, full natural limb mobility is rarely restored, often resulting in compensatory movements that lead to discomfort, inefficiency, and long-term physical strain. To address this issue, we propose a novel human-robot collaboration framework to mitigate compensatory mechanisms in upper-limb prosthesis users by exploiting their residual motion capabilities while respecting task requirements. Our approach introduces a personalised mobility model that quantifies joint-specific functional limitations and the cost of compensatory movements. This model is integrated into a constrained optimisation framework that computes optimal user postures for task performance, balancing functionality and comfort. The solution guides a collaborative robot to reconfigure the task environment, promoting effective interaction. We validated the framework using a new body-powered prosthetic device for single-finger amputation, which enhances grasping capabilities through synergistic closure with the hand but imposes wrist constraints. Initial experiments with healthy subjects wearing the prosthesis as a supernumerary finger demonstrated that a robotic assistant embedding the user-specific mobility model outperformed human partners in handover tasks, improving both the efficiency of the prosthesis user's grasp and reducing compensatory movements in functioning joints. These results highlight the potential of collaborative robots as effective workplace and caregiving assistants, promoting inclusion and better integration of prosthetic devices into daily tasks.