Overview
This work will focus on new algorithms for robotic exoskeletons and testing these in human subject tests. Individuals who have previously had a stroke will walk while wearing a robotic exoskeleton on a specialized treadmill as well as during other movement tasks (e.g. over ground, stairs, ramps). The study will compare the performance of the advanced algorithm with not using the device to determine the clinical benefit.
Description
The focus of this work is a proposed novel artificial intelligence (AI) system to self-adapt control policy in powered exoskeletons to aid deployment systems that personalize to individual patient gait. Individuals post stroke have a broad range of mobility challenges including asymmetric gait, substantially decreased SSWS, and reduced stability, and therefore have greatly impaired overall mobility independence in the community. The investigators expect the proposed novel controller, capable of personalization to such variable and asymmetric gait patterns, will have significant benefits towards increasing community independence and mobility for patients post stroke. Patients post stroke will be fit with a hip exoskeleton (in a powered and/or unpowered state) and proceed to walk on a treadmill or perform various movement tasks. The same tasks will be performed by the patients without wearing the hip exoskeleton to serve as a baseline. The investigators expect improved outcomes in the powered hip exoskeleton compared to the unpowered hip exoskeleton and baseline conditions.
Eligibility
Inclusion Criteria:
- Between 18-85 years of age
- Had a stroke at least 6 months prior to study involvement
- Are community dwelling, which means the participant does not live in an assisted living facility
- Are able to provide informed consent to participate in the study activities
- Can safely participate in the study activities (per self-report)
- Must have a Functional Ambulation Category (FAC) score of 3 or above, which means the participant can walk without the assistance of another person
Exclusion Criteria:
- Require a walker to walk independently
- Have a shuffling gait pattern
- Have a Functional Ambulation Category (FAC) score of 2 or lower, which means the participant requires the assistance of another person in order to walk
- Have a significant secondary deficit beyond stroke (e.g. amputation, legal blindness or other severe impairment or condition) that in the opinion of the Principal Investigator (PI), would likely affect the study outcome or confound the results