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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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Experimental Arm | Experimental | Training with the new "unified control framework" (the smart, adaptive robotic exoskeleton). |
|
| Active Comparator Arm | Active Comparator | Training with a "conventional controller" (the standard robotic exoskeleton controller). |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Unified Control Framework for Lower-Limb Powered Orthosis | Device | 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. |
| Measure | Description | Time Frame |
|---|---|---|
| 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). |
| Measure | Description | Time Frame |
|---|---|---|
| Acute Within-Session Changes in Spatial Gait Symmetry | Gait symmetry evaluated using the step length symmetry index (SI), calculated from lower-limb kinematics recorded by the exoskeleton's onboard joint encoders and/or motion capture data. This metric evaluates the immediate corrective effects on walking patterns. An SI of 0% represents perfect symmetry. | Baseline (Week 0) and weekly during the 12 training sessions across each 4-week intervention period. |
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Inclusion Criteria:
Cohort 2: Stroke Survivors (Clinical Efficacy Pilot)
Exclusion Criteria:
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Rehabilitation Laboratory in the Ford Robotics Building on the University of Michigan North Campus | Ann Arbor | Michigan | 48109 | United States |
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| ID | Term |
|---|---|
| D020521 | Stroke |
| ID | Term |
|---|---|
| D002561 | Cerebrovascular Disorders |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
| D009422 | Nervous System Diseases |
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|
| Conventional Robotic Controller | Device | 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. |
|
| Acute Within-Session Changes in Ground Reaction Force Symmetry | Force symmetry evaluated using the peak vertical ground reaction force ratio between the paretic and non-paretic limbs, measured via the exoskeleton's instrumented insoles and/or force plates. This evaluates the immediate impact of the control framework on weight-bearing symmetry. Data are expressed as a dimensionless ratio, where a value of 1.0 indicates perfect symmetry between limbs. Force is measured in units of Newtons. | 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 | Measurement of the peak angular displacement of the knee, hip and ankle joints (in degrees) during the sagittal plane gait cycle, captured by the exoskeleton's onboard joint encoders and/or a motion capture system. | Baseline (Week 0) and weekly during the 12 training sessions across each 4-week intervention period. |
| D014652 | Vascular Diseases |
| D002318 | Cardiovascular Diseases |