ReHabgame A non-immersive virtual reality rehabilitation system with applications in neuroscience
Shabnam Sadeghi Esfahlani, Tommy Thompson, Ali D. Parsa, Ian Brown,, Silvia Cirstea

TL;DR
This paper introduces ReHabgame, a non-immersive virtual reality system using Kinect and Myo for neurological rehabilitation, with adaptive gameplay and validated psychometric assessments.
Contribution
It presents a novel VR rehabilitation system with adaptive algorithms and psychometric validation for assessing postural control in neurological patients.
Findings
ReHabgame accurately quantifies postural control mechanisms.
The system's engagement scales meet Rasch model expectations.
Adaptive algorithms effectively tailor gameplay intensity.
Abstract
This paper proposes the use of a non-immersive virtual reality rehabilitation system ReHabgame developed using Microsoft Kinect and the Thalmic Labs Myo gesture control armband. The ReHabgame was developed based on two third-person video games that provide a feasible possibility of assessing postural control and functional reach tests. It accurately quantifies specific postural control mechanisms including timed standing balance, functional reach tests using real-time anatomical landmark orientation, joint velocity, and acceleration while end trajectories were calculated using an inverse kinematics algorithm. The game was designed to help patients with neurological impairment to be subjected to physiotherapy activity and practice postures of daily activities. The subjective experience of the ReHabgame was studied through the development of an Engagement Questionnaire (EQ) for…
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