Related Experiment Video
Updated: Oct 11, 2025
A Rehabilitation Program of Exoskeleton-assisted Body Weight-Supported Treadmill Training with Non-immersive Virtual Reality for Stroke Patients
Published on: May 16, 2025
Effects of different types of augmented feedback on intrinsic motivation and walking speed performance in
Saleh M Alhirsan1,2, Carmen E Capó-Lugo3, David A Brown4
1Rehabilitation Science Program, School of Health Professions, University of Alabama at Birmingham, USA.
Introduction:
During recovery from stroke, augmented performance feedback can be applied with simple displays of metrics, as well as enhanced with virtual reality (VR) and exergames. VR, as augmented feedback, can provided to enhance walking speed after six months of stroke onset. There are several mechanisms to induce improved motor performance and motivation. Our objective is to design a study to demonstrate the different effects of augmented feedback, simple VR and exergaming applications on motivation and walking speed performance in post stroke.
Methods:
Eighteen individuals with chronic stroke will be recruited and asked to walk as fast and safely as they can while on a robotic, user speed-driven treadmill (KineAssist-MX®) in three conditions: (1) with simple visual augmented feedback, but without a VR interface, (2) with a basic VR interface and (3) with a VR exergame. The main outcome measures are 30 s of fast walking speed and intrinsic motivation measured using the Intrinsic Motivation Inventory-Interest and Enjoyment Subscale. A within-subjects repeated measure ANOVA test and post hoc analysis will be used to determine the differences in changes of maximum walking speeds among the three performance conditions.
Discussion:
The additive impact of augmented feedback with or without VR and VR-exergames on motivation and walking speed during stroke rehabilitation is unknown, a gap we aim to address. Our findings will contribute key details regarding the effects of different types of augmented feedback on walking speed and intrinsic motivation and to the refinement of theoretical frameworks that guide the design and implementation of augmented feedback during recovery after stroke.
