Adaptive Hip Exoskeleton for Stroke Gait Enhancement

NCT05536739 | Completed FDA Device

• 3 other identifiers: H18182R03HD097740DP2HD111709
• Study Type: interventional
• Target: 12
• Locations: 1 country
• Sites: 1

Brief Summary

This work will focus on new algorithms for robotic exoskeletons and testing these in human subject tests. Individuals who have previously had a stroke will walk while wearing a robotic exoskeleton on a specialized treadmill as well as during other movement tasks (e.g. over ground, stairs, ramps). The study will compare the performance of the advanced algorithm with not using the device to determine the clinical benefit.

Conditions

Stroke

Keywords

Stroke

Outcome Measures

Primary Outcomes (3)

• Temporal Convolutional Network (TCN) model performance (Joint moment accuracy)

  This outcome represents the error with which the deep learning model embedded into our hip exoskeleton's microprocessor predicts hip joint moments in stroke patients. Specifically, the coefficient of determination (R²) is computed between the predicted hip joint moments and the ground truth measurements. Ground truth measurements are obtained from a laboratory-grade force plate system and inverse dynamics calculations. Hip joint moment predictions are made at a frequency of 200 Hz and compared to the laboratory-measured values. For these measures, higher R² values (closer to 1.0) indicate better correlation between predicted and actual hip joint moments. This metric provides a comprehensive assessment of the exoskeleton's ability to accurately estimate hip joint moments in stroke patients during tasks, with improved outcomes representing better assistive capabilities for the user.

  1 year

• Metabolic cost for level ground walking

  Metabolic energy expenditure will be quantified using an indirect calorimetry system (Parvo Medics, UT) that measures oxygen consumption (VO₂) and carbon dioxide production (VCO₂) during experimental tasks. Measurements will be collected from each participant during a 5-minute baseline standing period followed by level ground walking trials under three conditions: without the exoskeleton, with the exoskeleton in a powered state, and with the exoskeleton in an unpowered state. Metabolic cost will be calculated from respiratory gas exchange data using standard equations for energy expenditure.

  1 year

• Biological joint work

  Mechanical work performed by the lower limb joints will be quantified through biomechanical analysis of motion capture data. Joint moments and angular velocities will be derived through inverse dynamics and kinematics, respectively. Joint power, calculated as the product of joint moment and angular velocity, will be integrated with respect to time using trapezoidal integration to determine mechanical work. Positive and negative work will be calculated by separately integrating positive and negative joint powers, providing comprehensive quantification of joint energy generation and absorption at each joint during the movement tasks.

  1 year

Secondary Outcomes (8)

• Single limb stance time asymmetry index

  1 year

• Step Length Asymmetry index

  1 year

• 10 meter walk test (self-selected)

  1 year

• The timed up and go (TUG)

  1 year

• 6 Minute Walk Test

  1 year

Study Arms (1)

Hip Exoskeleton for Stroke Gait Assistance

EXPERIMENTAL

This study will be conducted on a sample population of stroke subjects (single arm). Subjects will be tested with either the powered hip exoskeleton and baseline or powered hip exoskeleton, unpowered hip exoskeleton, and baseline.

Device: Robotic hip exoskeleton; Other: No hip exoskeleton; Device: Unpowered hip exoskeleton

Interventions

Robotic hip exoskeleton DEVICE

The intervention is an experimental robotic hip exoskeleton in a powered state providing assistance to the user that has been previously developed by the team. It is used to improve walking gait performance.

Hip Exoskeleton for Stroke Gait Assistance

No hip exoskeleton OTHER

The intervention will serve as a baseline where participants will be asked to perform the tasks without wearing a hip exoskeleton.

Hip Exoskeleton for Stroke Gait Assistance

Unpowered hip exoskeleton DEVICE

The intervention is an experimental robotic hip exoskeleton in an unpowered state that has been previously developed by the team. It is used to improve walking gait performance.

Hip Exoskeleton for Stroke Gait Assistance

Eligibility Criteria

• Age: 18 Years - 85 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Between 18-85 years of age
• Had a stroke at least 6 months prior to study involvement
• Are community dwelling, which means the participant does not live in an assisted living facility
• Are able to provide informed consent to participate in the study activities
• Can safely participate in the study activities (per self-report)
• Must have a Functional Ambulation Category (FAC) score of 3 or above, which means the participant can walk without the assistance of another person

You may not qualify if:

• Require a walker to walk independently
• Have a shuffling gait pattern overground
• Have a Functional Ambulation Category (FAC) score of 2 or lower, which means the participant requires the assistance of another person in order to walk
• Have a significant secondary deficit beyond stroke (e.g. amputation, legal blindness or other severe impairment or condition) that in the opinion of the Principal Investigator (PI), would likely affect the study outcome or confound the results
• For exoskeleton-only studies, the exoskeleton device does not fit appropriately or safely, as determined by the research team during the fitting assessment.

Sponsors & Collaborators

• Georgia Institute of Technology: lead
• Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD): collaborator

Study Sites (1)

Exoskeleton and Prosthetic Intelligent Controls Lab

Atlanta, Georgia, 30332, United States

Location

MeSH Terms

Conditions

Stroke

Condition Hierarchy (Ancestors)

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

Study Officials

• Aaron Young, Ph.D.

  Georgia Institute of Technology

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: BASIC SCIENCE
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Model Details: The model used is a repeated measures single arm study

Study Record Dates

• First Submitted: September 8, 2022
• First Posted: September 13, 2022
• Study Start: May 21, 2025
• Primary Completion: August 29, 2025
• Study Completion: August 29, 2025
• Last Updated: March 30, 2026

Record last verified: 2026-03

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)