Virtual Reality-Integrated Limb Propulsion Visual Feedback System for End-Effector Robot-Assisted Stroke Rehabilitation
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 30
- 试验地点
- 1
- 主要终点
- Change in Spatiotemporal Gait Symmetry using the Zeno Walkway GaitMat
研究概览
简要总结
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.
详细描述
Introduction and Purpose:
People with hemiparetic stroke often exhibit gait asymmetry due to reduced propulsion from the paretic leg. This contributes to overreliance on the non-paretic leg and leads to inefficient, energy-consuming walking patterns. Traditional rehabilitation, including robot-assisted gait training, typically emphasizes repetitive motion but lacks a specific focus on propulsion, limiting its potential to promote neuroplasticity and symmetrical gait.
To address this limitation, the research team has developed a Virtual Reality (VR)-based visual feedback system that delivers real-time, individualized cues aimed at improving paretic limb propulsion. This system is integrated into the Morning Walk® end-effector rehabilitation robot developed by CUREXO. By encouraging active use of the paretic limb, the intervention is designed to reduce compensatory movement strategies and improve gait symmetry.
Study Objectives:
The primary objective is to evaluate the feasibility and effectiveness of this VR-enhanced limb propulsion training system. The study compares spatiotemporal gait parameters between individuals post-stroke and healthy controls, with the goal of determining whether real-time visual feedback can improve bilateral coordination and reduce asymmetry.
研究设计
- 研究类型
- Interventional
- 分配方式
- Non Randomized
- 干预模型
- Parallel
- 主要目的
- Basic Science
- 盲法
- None
入排标准
- 年龄范围
- 20 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •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.
排除标准
- •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).
结局指标
主要结局
Change in Spatiotemporal Gait Symmetry using the Zeno Walkway GaitMat
时间窗: Baseline (pre-training) and immediately post-training (same session)
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.
次要结局
- 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))