Biomechanics-Driven Optimization of Exoskeleton Configuration and Control for Knee Contact Force Reduction in Inclined Walking

Abstract

Knee osteoarthritis is a prevalent musculoskeletal disorder characterized by excessive internal joint loading, which is further exacerbated during demanding locomotor tasks such as inclined walking. While lower-limb exoskeletons offer potential for assistance, most existing designs are developed with generic objectives that do not explicitly target the reduction of knee contact force (KCF), a direct indicator of joint loading. This study proposes a biomechanics-driven optimization framework to identify the optimal configuration and control parameters of a knee exoskeleton for KCF reduction during inclined walking. The framework integrates human-exoskeleton interaction modeling, subject-specific musculoskeletal simulation, encompassing inverse dynamics, static optimization, and joint reaction analysis, and particle swarm optimization. Simulation results demonstrate that the optimized parameters achieved a decrease in mean KCF from 17.69 N/kg (no assistance) to 17.04 N/kg (pre-optimized assistance) and further to 16.60 N/kg (optimized assistance). Experimental validation $(\mathbf{1 5}^{\boldsymbol{\circ}}$, 0.6m/s) confirmed these findings, showing that optimized assistance reduced mean KCF from 17.58 N/kg to 16.45 N/kg. Furthermore, RMS muscle activations for the quadriceps and hamstrings were reduced by 1 6. 2 \% and 2 2. 0 \%. These findings demonstrate the framework's effectiveness in customizing exoskeleton parameters to alleviate internal joint loading, offering potentials for clinical gait assistance.