Peripheral Arterial DiseaseNCT04338815
Exoskeleton Variability Optimization
A study testing Exoskeleton Optimization and Endurance Evaluation in people with Peripheral Arterial Disease, run by University of Nebraska at 1 site in United States.
Trial summary
Exoskeletons, wearable devices that assist with walking, can improve mobility in clinical populations. With exoskeletons, it is crucial to optimize the assistance profile. Recent studies describe algorithms (i.e., human-in-the-loop) to optimize the assistance profile with real-time metabolic measurements. Read more about this study
- Who is it for?
- Ages 19 to 85 yearsHealthy volunteers can take part
- Conditions the study is for
- Peripheral Arterial Disease
- What is being tested?
- Exoskeleton Optimization and Endurance Evaluation
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 9 participants
- Where
- 1 siteUnited States
- Study dates
- 31 Jan 2022to 28 Mar 2025
- Phase
- Interventional
- Are there results?
- Yes, posted in the registrySummary in the doctors' view
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 19 to 85 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Ability to provide written consent
- Chronic claudication history
- Ankle-brachial index < 0.90 at rest
- Stable blood pressure, lipids, and diabetes for > 6 weeks
- Ability to walk on a treadmill for multiple five-minute spans
- Ability to fit in exoskeleton
Show all 9Show fewer
- Waist circumference 78 to 92 centimeters (31 to 36 inches)
- Thigh circumference 48 to 60 centimeters (19 to 24 inches)
- Minimal thigh length 28 centimeters (11 inches)
Who cannot join
- Resting pain or tissue loss due to peripheral artery disease (PAD, Fontaine stage III and IV)
- Foot ulceration
- Acute lower extremity event secondary to thromboembolic disease or acute trauma
- Walking capacity limited by diseases unrelated to PAD, such as:
- Neurological disorders
- Musculoskeletal disorders (arthritis, scoliosis, stroke, spinal injury, etc.)
Show all 20Show fewer
- History of ankle instability
- Knee injury
- Diagnosed joint laxity
- Lower limb injury
- Surgery within the past 12 months
- Joint replacement
- Pulmonary disease or breathing disorders
- Cardiovascular disease
- Vestibular disorder
- Acute injury or pain in lower extremity
- Current illness
- Inability to follow visual cues due to blindness
- Inability to follow auditory cues due to deafness
- Pregnant
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Exoskeleton Variability Optimization for Reducing Gait Variability for Patients With Peripheral Artery Disease
Exoskeletons, wearable devices that assist with walking, can improve mobility in clinical populations. With exoskeletons, it is crucial to optimize the assistance profile. Recent studies describe algorithms (i.e., human-in-the-loop) to optimize the assistance profile with real-time metabolic measurements. The needed duration of current human-in-the-loop (HITL) algorithms range from 20 minutes to 1 hour which is longer than the average duration that most patients with peripheral artery disease (PAD) can walk. Because of this limited walking duration, it is often not possible for patients with PAD to reach steady-state metabolic cost, which makes these measurements are not useful for optimizing exoskeletons. In this study, investigators intend to develop and evaluate HITL optimization methods for exoskeletons and use the information to design and evaluate a portable hip exoskeleton. Shorter and more clinically feasible HITL optimization strategies based on experiments in healthy adults might allow utilizing these optimization strategies to become available for patient populations such as patients with PAD.
Read the detailed description
Exoskeletons, wearable devices that assist with walking, can improve mobility in clinical populations. With exoskeletons, it is crucial to optimize the assistance profile. Recent studies describe algorithms (i.e., human-in-the-loop) to optimize the assistance profile with real-time metabolic measurements. The needed duration of current human-in-the-loop (HITL) algorithms range from 20 minutes to 1 hour which is longer than the average duration that most patients with peripheral artery disease (PAD) can walk. Because of this limited walking duration, it is often not possible for patients with PAD to reach steady-state metabolic cost, which makes these measurements are not useful for optimizing exoskeletons. Shorter and more clinically feasible HITL optimization strategies based on experiments in healthy adults might allow utilizing these optimization strategies to become available for patient populations such as patients with PAD.
This study will test different methods for optimizing exoskeletons. It will consist of an habituation session to the hip exoskeleton, an optimization session to find the optimal actuation settings using an algorithm that converges toward the optimum based on real-time measurements (human-in-the-loop algorithm) and a post-test at the end of optimization session to compare different conditions. The outcomes will be evaluated by surface electromyography, exoskeleton sensors, ground reaction force, walking speed, indirect calorimetry, and motion capture (Vicon).
- Conditions
- Peripheral Arterial Disease
- Being tested
- Exoskeleton Optimization, Endurance Evaluation
- Keywords
- Exoskeleton
- Medical subject headings
- Peripheral Arterial Disease
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Exoskeleton OptimizationOther
Participants will walk 10-minute trials while an optimization algorithm changes the assistance profile of the exoskeleton.
Endurance EvaluationOther
Participants will walk 2 trials at a speed of 1 meter per second until the participant indicates claudication or a maximum duration of 6 minutes, which ever comes first.
| Study group | Role | What they receive |
|---|---|---|
| Optimal Assistance Pattern | Experimental | An optimization algorithm will change the assistance pattern on the hip exoskeleton during walking sessions and the optimal assistance pattern will be determined when gait variability is minimized. Receives: Other: Exoskeleton Optimization |
| Endurance Effectds | Experimental | Endurance of participants using ground reaction force (Bertec treadmill), walking speed (Bertec treadmill), indirect calorimetry (Cosmed), and motion capture (Vicon) will be determined. Receives: Other: Endurance Evaluation |
What is being measured
The primary outcome is the main question the study is designed to answer.
Time to Convergence
Convergence is determined when the estimated optimal exoskeleton settings vary less than 10%. The time to convergence is measured.
Measured: 10 minutes
Peak Extension Timing
The time to peak extension moment of exoskeleton is measured by plotting the exoskeleton moment versus stride cycle percentage and finding the timing when the peak in the extension moment occurs expressed in percent of the stride cycle.
Measured: 20 seconds
Peak Flexion Timing
The time to peak flexion moment of exoskeleton is measured by plotting the flexion moment versus stride cycle percentage and finding the timing when the peak in the flexion moment occurs expressed in percent of the stride cycle.
Measured: 20 seconds
Largest Lyapunov Exponent
Largest Lyapunov exponent (the rate of separation of infinitesimally close trajectories) of lower limb kinematics is determined.
Largest Lyapunov exponent is calculated using Wolf's algorithm. The theoretical range is from zero to plus infinity. Zero indicates an entirely stable periodic movement pattern. Higher values indicate more unstable and chaotic movement patterns. Lower values are considered better, and higher values are considered worse for gait stability.
Measured: 20 seconds
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted8 Apr 2020
- Study start31 Jan 2022
- Primary completion28 Mar 2025
- Study completion28 Mar 2025
Why it stopped: The second arm was not completed since the first arm was not successful based on the convergence criteria.
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Posted resultsParticipant flow, outcome measures and adverse events reported by the sponsor.
- Other trials for Peripheral Arterial DiseaseStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Basic science
- Allocation
- Non-randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Enrolment
- 9 participants (actual)
Sponsor and investigators
- Lead sponsor
- University of Nebraska
- Sponsor type
- University, hospital or other
- Collaborators
- National Institute of General Medical Sciences (NIGMS)
- Responsible party
- Sponsor
- Investigators
- Philippe Malcolm, Principal investigator, University of Nebraska
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04338815
- Sponsor's protocol ID
- 0376-19-FB
- Other IDs
- P20GM109090
- Status last verified
- Jun 2025
- First submitted
- 3 Apr 2020
- Last updated
- 19 Jun 2025
- Results posted
- Yes, on ClinicalTrials.gov
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 19 Jun 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Exoskeleton Variability Optimization for Reducing Gait Variability for Patients With Peripheral Artery Disease
- ClinicalTrials.gov ID
- NCT04338815
- Acronym / sponsor ID
- 0376-19-FB
- Conditions
- Peripheral Arterial Disease
- Keywords
- Exoskeleton
- Study type
- Interventional
- Recruitment status
- TerminatedReason stopped: The second arm was not completed since the first arm was not successful based on the convergence criteria.
- Enrolment
- 9 participants (actual)
- Lead sponsor
- University of NebraskaUniversity, hospital or other
- Collaborators
- National Institute of General Medical Sciences (NIGMS)
- Study start
- 31 Jan 2022 (actual)
- Primary completion
- 28 Mar 2025 (actual)
- Study completion
- 28 Mar 2025 (actual)
- First posted
- 8 Apr 2020 (actual)
- Results
- Posted 19 Jun 2025
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Exoskeletons, wearable devices that assist with walking, can improve mobility in clinical populations. With exoskeletons, it is crucial to optimize the assistance profile. Recent studies describe algorithms (i.e., human-in-the-loop) to optimize the assistance profile with real-time metabolic measurements. The needed duration of current human-in-the-loop (HITL) algorithms range from 20 minutes to 1 hour which is longer than the average duration that most patients with peripheral artery disease (PAD) can walk. Because of this limited walking duration, it is often not possible for patients with PAD to reach steady-state metabolic cost, which makes these measurements are not useful for optimizing exoskeletons. In this study, investigators intend to develop and evaluate HITL optimization methods for exoskeletons and use the information to design and evaluate a portable hip exoskeleton. Shorter and more clinically feasible HITL optimization strategies based on experiments in healthy adults might allow utilizing these optimization strategies to become available for patient populations such as patients with PAD.
Detailed description
Exoskeletons, wearable devices that assist with walking, can improve mobility in clinical populations. With exoskeletons, it is crucial to optimize the assistance profile. Recent studies describe algorithms (i.e., human-in-the-loop) to optimize the assistance profile with real-time metabolic measurements. The needed duration of current human-in-the-loop (HITL) algorithms range from 20 minutes to 1 hour which is longer than the average duration that most patients with peripheral artery disease (PAD) can walk. Because of this limited walking duration, it is often not possible for patients with PAD to reach steady-state metabolic cost, which makes these measurements are not useful for optimizing exoskeletons. Shorter and more clinically feasible HITL optimization strategies based on experiments in healthy adults might allow utilizing these optimization strategies to become available for patient populations such as patients with PAD.
This study will test different methods for optimizing exoskeletons. It will consist of an habituation session to the hip exoskeleton, an optimization session to find the optimal actuation settings using an algorithm that converges toward the optimum based on real-time measurements (human-in-the-loop algorithm) and a post-test at the end of optimization session to compare different conditions. The outcomes will be evaluated by surface electromyography, exoskeleton sensors, ground reaction force, walking speed, indirect calorimetry, and motion capture (Vicon).
Study design
- Primary purpose
- Basic science
- Allocation
- Non-randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Optimal Assistance Pattern | Experimental | Other: Exoskeleton OptimizationAn optimization algorithm will change the assistance pattern on the hip exoskeleton during walking sessions and the optimal assistance pattern will be determined when gait variability is minimized. |
| Endurance Effectds | Experimental | Other: Endurance EvaluationEndurance of participants using ground reaction force (Bertec treadmill), walking speed (Bertec treadmill), indirect calorimetry (Cosmed), and motion capture (Vicon) will be determined. |
Who may qualify
- Ages
- 19 to 85 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (9 listed)
- Ability to provide written consent
- Chronic claudication history
- Ankle-brachial index < 0.90 at rest
- Stable blood pressure, lipids, and diabetes for > 6 weeks
- Ability to walk on a treadmill for multiple five-minute spans
Key exclusion criteria (20 listed)
- Resting pain or tissue loss due to peripheral artery disease (PAD, Fontaine stage III and IV)
- Foot ulceration
- Acute lower extremity event secondary to thromboembolic disease or acute trauma
- Walking capacity limited by diseases unrelated to PAD, such as:
- Acute injury or pain in lower extremity
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Exoskeleton OptimizationParticipants will walk 10-minute trials while an optimization algorithm changes the assistance profile of the exoskeleton. | Other | Optimal Assistance Pattern |
| Endurance EvaluationParticipants will walk 2 trials at a speed of 1 meter per second until the participant indicates claudication or a maximum duration of 6 minutes, which ever comes first. | Other | Endurance Effectds |
Primary outcome
Time to Convergence
Time frame: 10 minutes
Convergence is determined when the estimated optimal exoskeleton settings vary less than 10%. The time to convergence is measured.
Peak Extension Timing
Time frame: 20 seconds
The time to peak extension moment of exoskeleton is measured by plotting the exoskeleton moment versus stride cycle percentage and finding the timing when the peak in the extension moment occurs expressed in percent of the stride cycle.
Peak Flexion Timing
Time frame: 20 seconds
The time to peak flexion moment of exoskeleton is measured by plotting the flexion moment versus stride cycle percentage and finding the timing when the peak in the flexion moment occurs expressed in percent of the stride cycle.
Largest Lyapunov Exponent
Time frame: 20 seconds
Largest Lyapunov exponent (the rate of separation of infinitesimally close trajectories) of lower limb kinematics is determined. Largest Lyapunov exponent is calculated using Wolf's algorithm. The theoretical range is from zero to plus infinity. Zero indicates an entirely stable periodic movement pattern. Higher values indicate more unstable and chaotic movement patterns. Lower values are considered better, and higher values are considered worse for gait stability.
Results and safety
Loading the posted results from ClinicalTrials.gov…
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 19 Jun 2025.
- Posted resultsParticipant flow, baseline, all outcome measures and adverse events.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Philippe Malcolm principal investigator
University of Nebraska
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Exoskeleton Optimization and Endurance Evaluation in people with Peripheral Arterial Disease, run by University of Nebraska at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 9 inclusion and 20 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: stopped early, as of the sponsor's last update on 19 Jun 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Yes. Results are posted in the registry (first posted 19 Jun 2025). A summary is in the For doctors view, and the full results are on ClinicalTrials.gov.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Time to Convergence (time frame: 10 minutes). The study lists 4 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 19 Jun 2025.