Effects of Rehabilitation Robots-Morning Walk in Individuals With Hemiparesis

Stroke Clinical Trial

Official title: Effects of End-Effector Type Rehabilitation Robots-Morning Walk on Symmetrical Walking Patterns in Individuals With Hemiparesis

Status Recruiting

Clinical Trial Summary

In this study, our objective is to explore and evaluate interventions to improve the process of recovery following a stroke. The main focus is on enhancing symmetrical walking patterns in adults who have experienced neurological deficits due to a stroke. The primary tool will be an end-effector type rehabilitation robot, the Morning Walk®. This robot has been specifically designed to assist in enhancing symmetrical walking patterns for individuals recovering from a stroke Morning Walk® has received approval from the FDA, meaning it meets stringent safety and efficacy standards.

Clinical Trial Description

Total forty participants (20 stroke vs 20 healthy individuals) will sign a consent form that is pre-approved by the Institutional Review Board at the participating facilities, which states the purpose of the study, an explanation of the procedures, benefits and risks for the participant, a confidentiality statement, and a refusal/withdrawal policy.

This study will assess the feasibility of end-effector rehabilitation robots, specifically Morning Walk®, to optimize training outcomes and improve symmetry in individuals with stroke.

1. Access the severity of functional and balance capacity prior to gait training. Stroke or healthy participants will first be asked questions about their medical history, physical functionality, and overall well-being. Participants will be equipped with an armband or chest strap to monitor their heart rate. Functional capacity will be assessed using walking tests on the Zeno Walkway system, which evaluates gait speed and spatiotemporal gait parameters during overground walking trials. During the testing process, participants will be recorded on video.

2. Develop the training protocol for the end-effector rehabilitation robot, Morning Walk.

Prior to the end-effector robot training, Investigators will attach six Delsys wireless electromyographic sensors (Delsys Inc, Natick, MA) to analyze muscle activity in the lower extremities. Additionally, stroke or healthy participants will be equipped with the Tekscan In-Shoes system (Tekscan, Inc., South Boston) to assess temporal events related to foot positioning during training, such as limb loading time. During the end-effector robot training, a saddle-type weight support and secure strap system will be employed to prevent loss of balance or falls. Following an appropriate warm-up and familiarization with the end-effector robot training, various walking parameters of Morning Walk, such as pace, stride length, step height, and initial contact angle, will be examined to achieve balanced loading times between the paretic and non-paretic sides in stroke participants. Training parameters such as step length, step height, and joint angle can be independently adjusted for the paretic and non-paretic sides in stroke patients, and for the dominant and non-dominant sides in healthy individuals. This approach allows for the restriction of movement in the non-paretic or non-dominant side, thereby encouraging the activity of the paretic or dominant side during training. The adaptation training parameters will be adjusted according to the participant's walking capacity. During the training session, participants will be recorded on video.

3. Assessing the Immediate Post-Adaptation Effect of Morning Walk Training on the Ground.

Stroke or healthy participants will be asked to on the Zeno Walkway system to evaluate gait speed and spatiotemporal gait parameters during overground walking trials. During the testing process, participants will be recorded on video. ;

Related Conditions & MeSH terms

• Healthy Volunteers
• Paresis
• Stroke

• NCT number: NCT06374706
• Study type: Interventional
• Source: The University of Texas Medical Branch, Galveston
• Contact: Mansoo Ko, Ph.D.
• Phone: 3522782144
• Email: mako@utmb.edu
• Status: Recruiting
• Phase: N/A
• Start date: May 30, 2024
• Completion date: May 30, 2025