Virtual Reality-Integrated Propulsion Feedback for Stroke Rehab

NCT07087743 | Recruiting

• 1 other identifier: 25-0065
• Study Type: interventional
• Target: 30
• Locations: 1 country
• Sites: 1

Brief Summary

This study evaluates a novel Virtual Reality (VR)-integrated visual feedback system designed to enhance limb propulsion during robot-assisted gait rehabilitation in individuals post-stroke. In collaboration with CUREXO, a rehabilitation robotics company, the system is embedded within the Morning Walk® end-effector robot and provides real-time visual feedback to facilitate symmetrical use of the paretic and non-paretic limbs. The goal is to address gait asymmetry commonly observed in hemiparetic stroke survivors by promoting improved paretic leg propulsion, which is a key contributor to forward movement during walking. A total of 30 participants (15 stroke, 15 healthy controls) aged 20 years or older will undergo single-session gait training using the VR-robot system. Participants will be assessed using spatiotemporal gait parameters, muscle activity, foot pressure, and vertical ground reaction forces. Additional safety measures-including a saddle-type weight support and real-time heart rate monitoring via smartwatch-are implemented to ensure a safe and controlled training environment. This study aims to test the feasibility and effectiveness of this VR-based system in improving gait symmetry and functional walking capacity in people recovering from stroke.

Conditions

Stroke; Robot Assisted Gait Training; Virtual Reality

Keywords

Propulsion Feedback; Gait Rehabilitation; Paretic Leg; Virtual Reality; End-Effector Robot

Outcome Measures

Primary Outcomes (1)

• Change in Spatiotemporal Gait Symmetry using the Zeno Walkway GaitMat

  Spatiotemporal gait parameters will be collected using the Zeno Walkway GaitMat before and after a single session of VR-based gait training. Gait spatiotemporal parameters will be calculated from the ratio of step lengths (paretic/non-paretic in stroke group; left/right in healthy group). The step length will be compared pre- and post-training.

  Baseline (pre-training) and immediately post-training (same session)

Secondary Outcomes (2)

• Change in Peak Propulsive Force (Paretic vs. Non-Paretic Limb)

  Baseline and immediately post-training (same session)

• Change in Lower Extremity Muscle Activity

  Baseline and immediately post-training (same session)

Study Arms (2)

Post-Stroke Group

EXPERIMENTAL

Individuals who have had a stroke will complete a single session of VR-integrated gait training using the Morning Walk® end-effector robot. Gait performance will be evaluated before and after training.

Behavioral: VR-Based Gait Training with End-Effector Robot

Healthy Group

EXPERIMENTAL

Healthy participants will undergo the same single-session VR-integrated gait training using the Morning Walk® end-effector robot. Pre- and post-training assessments will be conducted.

Behavioral: VR-Based Gait Training with End-Effector Robot

Interventions

VR-Based Gait Training with End-Effector Robot BEHAVIORAL

A single-session gait training protocol using the Morning Walk® end-effector robot with real-time virtual reality visual feedback to encourage paretic limb propulsion and symmetrical gait. This intervention is intended to study participants' behavioral and biomechanical responses to the VR feedback, not to evaluate the robot as a device.

Healthy Group; Post-Stroke Group

Eligibility Criteria

• Age: 20 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Adults aged 20 years or older.
• For post-stroke participants:
• Diagnosis of stroke at least 1 month prior to participation.
• Able to walk at least 10 meters with or without assistive devices.
• For healthy participants:
• ° Must walk independently without assistive devices.

You may not qualify if:

• Individuals with a life expectancy of less than one year.
• Comatose individuals.
• Individuals unable to follow three-step commands.
• Individuals with lower limb amputation.
• Individuals with poorly controlled diabetes (e.g., foot ulceration).
• Individuals with legal blindness.
• Individuals with progressive neurological conditions.
• Medically unstable individuals.
• Individuals with significant musculoskeletal impairments.
• Individuals with congestive heart failure or unstable angina.
• Individuals with peripheral vascular disease.
• Individuals with severe neuropsychiatric disorders (e.g., dementia, cognitive deficits, or severe depression).

Sponsors & Collaborators

• The University of Texas Medical Branch, Galveston: lead

Study Sites (1)

University of Texas Medical Branch

Galveston, Texas, 77555, United States

RECRUITING

MeSH Terms

Conditions

Stroke

Condition Hierarchy (Ancestors)

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

Central Study Contacts

Mansoo Ko, PhD

CONTACT

409-747-1617; mako@utmb.edu

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NON RANDOMIZED
• Masking: NONE
• Purpose: BASIC SCIENCE
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Model Details: This is a mixed design study with two distinct populations: individuals post-stroke and healthy controls. All participants undergo a single session of VR-based gait training with an end-effector robot. Pre- and post-intervention measures are collected to evaluate within-subject changes and between-group differences.

Study Record Dates

• First Submitted: July 9, 2025
• First Posted: July 28, 2025
• Study Start: July 25, 2025
• Primary Completion (Estimated): December 27, 2026
• Study Completion (Estimated): December 30, 2026
• Last Updated: April 1, 2026

Record last verified: 2026-03

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)