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About 80% of stroke survivors struggle to walk due to weakness on one side of the body, which impairs mobility and leads to a compensatory gait patterns that may limit recovery and ability in the affected leg. Despite the best efforts of clinicians, this compensatory strategy typically persists following gait rehabilitation. Innovative approaches are needed to more effectively address walking deficits experienced by patients after stroke.
This research project will leverage the knowledge we gained from developing a complex robotic treadmill, the KineAssist MX (funded in a previous cycle), in order to refine and rigorously test a simpler, clinically-viable collaborative machine — which we will call the ResistX S/B — focused specifically on re-training force generation in the paretic limb.
Within the current funding cycle (2018-2023), we will:
- Fabricate an innovative split-belt treadmill system that allows backward-directed, real-time-adaptive, resistive forces applied to the pelvis; then validate the use of this system to determine personalized, split-belt speeds and pelvic resistance levels that maximize gait training
- Prescribe and evaluate a machine-assisted, gait training intervention for participants post-stroke that will last 12 weeks
- Participate in the collective observational study on factors influencing uptake at the Shirley Ryan AbilityLab
Team Members
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David A. Brown, PT, PhD, University of Alabama at Birmingham
Christopher P. Hurt, PhD, University of Alabama at Birmingham
Stacey Kelpke, PhD, Southern Research Institute (Birmingham, AL)
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The contents of this webpage were developed under a grant from the National Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR grant number 90REGE0005-01-00). NIDILRR is a Center within the Administration for Community Living (ACL), Department of Health and Human Services (HHS). The contents of this webpage do not necessarily represent the policy of NIDILRR, ACL, or HHS, and you should not assume endorsement by the Federal Government.
This project is part of the Collaborative Machines Enhancing Therapies (COMET) Rehabilitation Engineering Research Center.