A simulation-based framework with a proprioceptive musculoskeletal model for evaluating the rehabilitation exoskeleton system

Various rehabilitation exoskeletons have been designed to help people regain normal gait from stroke effects. However, the evaluation and further optimization of these exoskeletons are not convenient and usually need complicated experimental works. The present study aims to establish a simulation-based method with a proprioceptive musculoskeletal model to conveniently evaluate the efficiency of a self-developed exoskeleton for further optimization.

Three volunteers who suffer from dyskinesia due to stroke were recruited for gait experiments with and without the self-develop exoskeleton. The corresponding simulations were implemented based on the proprioceptive model, the exoskeleton model, and the input kinematic data obtained from the experiments. The joint angles, muscle activations, and metabolic costs as well as the proprioceptor feedback stimulation were extracted for comparative analysis.

Several positive effects of the exoskeleton were noted based on the simulation results when using it to aid the patients' rehabilitation during the gait training. The CORA scores of the patients' joint angle to the normal data increased by 11.6~37.8% with the assistance of the exoskeleton. The wave frequency of proprioceptive feedback stimulation that can be directly correlated to the neural rehabilitation obviously inclined during a gait cycle. The muscle activations were also rearranged to better support the patient's walk when using the exoskeleton, while the metabolic costs were reduced for all the patients.

In summary, the present simulation-based method can be practical for pre-evaluation and optimization of various exoskeleton design in the future.