This Study Evaluates the Use of a Data-driven Lower Limb Exoskeleton Controller for Stroke Rehabilitation.
From Stroke Rehabilitation to Independence: An Impairment-Aware Control Framework for Adaptive Exoskeleton Assistance
1 other identifier
interventional
20
1 country
1
Brief Summary
The goal of this clinical trial is to test a new, impairment-aware robotic control software framework to see if its smart adaptation can improve walking recovery in healthy adults and chronic stroke survivors. . The main questions it aims to answer are: Can the new control software safely use sensors and machine learning to predict and instantly adapt to a user's specific walking needs? Does training with a robotic device driven by this new adaptive control framework improve walking speed and overall mobility in stroke survivors? Researchers will compare a lower-limb orthosis operating under the new "smart" control software (which adapts to the user's impairment) to the same device operating under a standard, non-adaptive controller (which uses rigid or fixed assistance) to see if the new control approach leads to greater improvements in walking ability. Participants will: Walk on treadmills, flat walkways, or stairs while wearing a robotic leg orthosis driven by the different control software systems being tested. Wear small tracking tools (like reflective motion-capture markers and muscle activity sensors) so researchers can precisely measure how their movements interact with each control program. Complete standard walking tests to measure their walking speed and overall mobility under each software condition.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at below P25 for not_applicable stroke
Started Oct 2026
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
May 19, 2026
CompletedFirst Posted
Study publicly available on registry
June 1, 2026
CompletedStudy Start
First participant enrolled
October 1, 2026
CompletedPrimary Completion
Last participant's last visit for primary outcome
December 31, 2027
ExpectedStudy Completion
Last participant's last visit for all outcomes
December 31, 2027
June 1, 2026
May 1, 2026
1.2 years
May 19, 2026
May 27, 2026
Conditions
Outcome Measures
Primary Outcomes (2)
Walking Speed
A standardized clinical assessment used to determine short-distance walking speed over a 10-meter course. This metric evaluates the preliminary clinical efficacy of the unified control framework compared to the conventional controller in chronic stroke survivors.
Baseline (Week 0), Post-Intervention Phase 1 (Week 4), Post-Washout / Pre-Intervention Phase 2 (Week 8), and Post-Intervention Phase 2 (Week 12).
Functional Mobility and Balance
A clinical performance-based measure used to assess dynamic balance, turning agility, and functional mobility. The test measures the time (in seconds) taken for a participant to rise from a chair, walk 3 meters, turn around, walk back, and sit down.
Baseline (Week 0), Post-Intervention Phase 1 (Week 4), Post-Washout / Pre-Intervention Phase 2 (Week 8), and Post-Intervention Phase 2 (Week 12).
Secondary Outcomes (3)
Acute Within-Session Changes in Spatial Gait Symmetry
Baseline (Week 0) and weekly during the 12 training sessions across each 4-week intervention period.
Acute Within-Session Changes in Ground Reaction Force Symmetry
Baseline (Week 0) and weekly during the 12 training sessions across each 4-week intervention period.
Acute Within-Session Changes in Joint Range of Motion
Baseline (Week 0) and weekly during the 12 training sessions across each 4-week intervention period.
Study Arms (2)
Experimental Arm
EXPERIMENTALTraining with the new "unified control framework" (the smart, adaptive robotic exoskeleton).
Active Comparator Arm
ACTIVE COMPARATORTraining with a "conventional controller" (the standard robotic exoskeleton controller).
Interventions
An AI-driven, machine learning-based control software integrated into a wearable lower-limb powered orthosis. The system utilizes a Bayesian Neural Network (BNN) to analyze a user's pathological walking patterns (kinematics) in real-time via onboard sensors. Based on this real-time performance, the device dynamically modulates its physical assistance along a seamless continuum. It automatically transitions between stiff corrective guidance (position-based gait training) when the user struggles, and compliant, volitional torque support (torque-based assistance) as the user's independent walking ability improves.
A standard control paradigm for lower-limb powered orthoses that provides non-adaptive physical assistance during gait training. Depending on the trial block, the device operates in one of two static modalities: either rigid position-based gait training (GT) that physically guides the patient's limbs through a fixed, predetermined trajectory regardless of effort, or torque-based volitional augmentation (VA) that proportionally amplifies existing muscle output or ground reaction forces. Unlike the experimental intervention, this controller cannot interpret kinematics in real-time or dynamically modulate assistance along a continuous spectrum based on the user's instantaneous performance.
Eligibility Criteria
You may qualify if:
- Cohort 1: Able-Bodied Participants (Initial Validation)
- Healthy young adults.
- No history of neurological, orthopedic, or cardiovascular impairments affecting gait or balance.
- Able to walk independently without assistive devices.
- Cohort 2: Stroke Survivors (Clinical Efficacy Pilot)
- Individuals with a documented history of chronic stroke.
- Persistent unilateral lower-limb motor impairment resulting in a pathological gait pattern (heterogeneous gait deficits).
- Stable medical condition allowing for participation in intensive physical rehabilitation tasks.
- Able to provide informed consent.
You may not qualify if:
- Severe cognitive or communication impairments that prevent the participant from following safety instructions or reporting discomfort.
- Co-existing neurological conditions (other than stroke) that independently impair locomotion (e.g., Parkinson's disease, Multiple Sclerosis).
- Severe lower-limb joint contractures or orthopedic conditions that mechanically restrict the safe range of motion of the robotic orthosis.
- Skin breakdowns, open wounds, or severe unhealed lesions at the contact points where the powered orthosis interfaces with the lower limbs.
- Any medical contraindication to intensive walking exercise or treadmill training (e.g., unstable angina, severe unmanaged cardiovascular disease).
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Rehabilitation Laboratory in the Ford Robotics Building on the University of Michigan North Campus
Ann Arbor, Michigan, 48109, United States
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- RANDOMIZED
- Masking
- NONE
- Purpose
- TREATMENT
- Intervention Model
- CROSSOVER
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Professor
Study Record Dates
First Submitted
May 19, 2026
First Posted
June 1, 2026
Study Start
October 1, 2026
Primary Completion (Estimated)
December 31, 2027
Study Completion (Estimated)
December 31, 2027
Last Updated
June 1, 2026
Record last verified: 2026-05