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NCT Number: NCT07616167

This Study Evaluates the Use of a Data-driven Lower Limb Exoskeleton Controller for Stroke Rehabilitation.

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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Key information

Conditions

Stroke Brain Diseases Cardiovascular Diseases Central Nervous System Diseases Cerebrovascular Disorders Nervous System Diseases Vascular Diseases

Age range

18 year–80 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Rehabilitation Laboratory in the Ford Robotics Building on the University of Michigan North Campus

Ann Arbor, Michigan, 48109, United States

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • 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.

Exclusion criteria

  • 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).

Treatment and study plan

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.

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.

Primary outcomes

  1. Walking Speed

    Time frame: Baseline (Week 0), Post-Intervention Phase 1 (Week 4), Post-Washout / Pre-Intervention Phase 2 (Week 8), and Post-Intervention Phase 2 (Week 12).

    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.

  2. Functional Mobility and Balance

    Time frame: Baseline (Week 0), Post-Intervention Phase 1 (Week 4), Post-Washout / Pre-Intervention Phase 2 (Week 8), and Post-Intervention Phase 2 (Week 12).

    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.

Secondary outcomes

  1. Acute Within-Session Changes in Spatial Gait Symmetry

    Time frame: Baseline (Week 0) and weekly during the 12 training sessions across each 4-week intervention period.

    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.

  2. Acute Within-Session Changes in Ground Reaction Force Symmetry

    Time frame: Baseline (Week 0) and weekly during the 12 training sessions across each 4-week intervention period.

    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.

  3. Acute Within-Session Changes in Joint Range of Motion

    Time frame: Baseline (Week 0) and weekly during the 12 training sessions across each 4-week intervention period.

    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.

Sponsors and collaborators

Lead sponsor

University of Michigan

Other

Registry information

Official study title

From Stroke Rehabilitation to Independence: An Impairment-Aware Control Framework for Adaptive Exoskeleton Assistance

Important dates

Study start
2026
Primary completion
2027
Study completion
2027
First posted
Jun 1, 2026
Registry last updated
Jun 1, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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