Virtual reality to maximize function for hand and arm rehabilitation: exploration of neural mechanisms.

Stud Health Technol Inform

Doctoral Programs in Physical Therapy, Department of Rehabilitation and Movement Science, University of Medicine and Dentistry of New Jersey, Newark, USA.

Published: September 2009

Stroke patients report hand function as the most disabling motor deficit. Current evidence shows that learning new motor skills is essential for inducing functional neuroplasticity and functional recovery. Adaptive training paradigms that continually and interactively move a motor outcome closer to the targeted skill are important to motor recovery. Computerized virtual reality simulations when interfaced with robots, movement tracking and sensing glove systems, are particularly adaptable, allowing for online and offline modifications of task based activities using the participant's current performance and success rate. We have developed a second generation system that can exercise the hand and the arm together or in isolation and provide for both unilateral and bilateral hand and arm activities in three-dimensional space. We demonstrate that by providing haptic assistance for the hand and arm and adaptive anti-gravity support, the system can accommodate patients with lower level impairments. We hypothesize that combining training in virtual environments (VE) with observation of motor actions can bring additional benefits. We present a proof of concept of a novel system that integrates interactive VE with functional neuroimaging to address this issue. Three components of this system are synchronized, the presentation of the visual display of the virtual hands, the collection of fMRI images and the collection of hand joint angles from the instrumented gloves. We show that interactive VEs can facilitate activation of brain areas during training by providing appropriately modified visual feedback. We predict that visual augmentation can become a tool to facilitate functional neuroplasticity.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4554695PMC

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