Exoskeleton Variability Optimization

NCT ID: NCT04338815

Last Updated: 2025-06-19

Basic Information

• Recruitment Status: TERMINATED
• Clinical Phase: NA
• Total Enrollment: 9 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2022-01-31
• Study Completion Date: 2025-03-28

Brief 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. 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).

Conditions

Peripheral Arterial Disease

Study Design

• Allocation Method: NON_RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: BASIC_SCIENCE
• Blinding Strategy: NONE

Study Groups

Optimal Assistance Pattern

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.

Group Type: EXPERIMENTAL

Exoskeleton Optimization

Intervention Type: OTHER

Participants will walk 10-minute trials while an optimization algorithm changes the assistance profile of the exoskeleton.

Endurance Effectds

Endurance of participants using ground reaction force (Bertec treadmill), walking speed (Bertec treadmill), indirect calorimetry (Cosmed), and motion capture (Vicon) will be determined.

Group Type: EXPERIMENTAL

Endurance Evaluation

Intervention Type: OTHER

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.

Interventions

Exoskeleton Optimization

Participants will walk 10-minute trials while an optimization algorithm changes the assistance profile of the exoskeleton.

Intervention Type: OTHER

Endurance Evaluation

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.

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

• 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

• 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)

Exclusion Criteria

• 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.)
• 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

• Minimum Eligible Age: 19 Years
• Maximum Eligible Age: 85 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

National Institute of General Medical Sciences (NIGMS)

NIH

Sponsor Role: collaborator

University of Nebraska

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Philippe Malcolm

Role: PRINCIPAL_INVESTIGATOR

University of Nebraska

Locations

University of Nebraska Omaha

Omaha, Nebraska, United States

Countries

United States

Provided Documents

Document Type: Study Protocol and Statistical Analysis Plan

View Document

Document Type: Informed Consent Form

View Document

Other Identifiers

P20GM109090

Identifier Type: NIH

Identifier Source: secondary_id

View Link

0376-19-FB

Identifier Type: -

Identifier Source: org_study_id