4.7 Article

A Model-Based Analysis of Supraspinal Mechanisms of Inter-Leg Coordination in Human Gait: Toward Model-Informed Robot-Assisted Rehabilitation

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNSRE.2021.3072771

Keywords

Brain modeling; Legged locomotion; Perturbation methods; Adaptation models; Data models; Stroke (medical condition); Hip; Rehabilitation robotics; human gait; stroke; balance; modeling

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This research provides new insights into the gait rehabilitation of stroke survivors, with the discovery of muscle-neural models and control variables that could improve current rehabilitation methods and enhance patients' mobility and quality of life.
Stroke survivors are often left suffering from gait instability due to hemiparesis. This gait dysfunction can lead to higher fall rates and an overall decrease in quality of life. Though there are many post-stroke gait rehabilitation methods in use currently, none of them allow patients to regain complete functionality. Interlimb coordination is one of the main mechanisms of walking and is usually overlooked in most post-stroke gait rehabilitation protocols. This work attempts to help further understand the mechanism of interlimb coordination and how the brain is involved in it, studying the contralateral response to unilateral stiffness perturbations. A unique robotic device, the Variable Stiffness Treadmill (VST), is used in conjunction with a pre-established neuromuscular gait model to analyze for the first time the supraspinal control mechanisms involved in inter-leg coordination induced after unilateral perturbations. The attempt to explain the observed kinematic and muscular activation data via the gait model results in the identification of two control variables that seem to play an important role in gait stability and recovery after perturbations: the target angle of attack and target hip to ankle span. This is significant because these two parameters are directly related to longer stride length and larger foot clearance during swing phase. Both variables work toward correcting common issues with hemiparetic gait, such as a shorter stride and toe drag during swing phase of the paretic leg. The results of this work could aid in the design of future model-based stroke rehabilitation methods that would perturb the subject in a systematic way and allow targeted interventions with specific functional outcomes on gait. Additionally, this work-along with future studies-could assist in improving controllers for robust bipedal robots as well as our understanding of how the brain controls balance during perturbed walking.

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