Optimizing Hand Rehabilitation Post Stroke Using Interactive Virtual Environments
Optimizing Hand Rehabilitation Post Stroke Using Interactive Virtual Environments
This study investigates the effects of intensive, high dosage task and impairment based training of the hemiparetic hand, using haptic robots integrated with complex gaming and virtual reality simulations. There is a time-limited period of post-ischemic heightened neuronal plasticity during which intensive training may optimally affect the recovery of motor skills, indicating that the timing of rehabilitation is as important as the dosing. However, recent literature indicates a controversy regarding both the value of intensive, high dosage as well as the optimal timing for therapy in the first two months after stroke. This study is designed to empirically investigate this controversy. It is evident that providing additional, intensive therapy during the acute rehabilitation stay is more complicated to implement and difficult for patients to tolerate, than initiating it in the outpatient setting, immediately after discharge. The robotic/VR system is specifically designed to deliver hand and arm training when motion and strength are limited, using adaptive algorithms to drive individual finger movement, gain adaptation and workspace modification to increase finger and arm range of motion, and haptic and visual feedback from mirrored movements to reinforce motor networks in the lesioned hemisphere.
This study investigates the effects of high dosage task and impairment based training of the hemiparetic hand, using haptic robots integrated with complex gaming and virtual reality simulations on recovery and function of the hand, when the training is initiated within early period of heightened plasticity. The intervention uses two training systems. NJIT-RAVR consists of a data glove combined with the Haptic Master robot that provides tracking of movements in a 3D workspace and enables programmable haptic effects, such as variable anti-gravity support, springs and dampers, and various haptic objects. The NJIT-TrackGlove consists of a robotic hand exoskeleton to provide haptic effects or assistance and an instrumented glove for finger angle tracking, and an arm tracking system to track hand and arm position and orientation. Using programmable software and custom bracing we enable use of this system for patients with a broad set of impairments and functional abilities. A library of custom-designed impairment and task-based simulations that train arm transport and hand manipulation, together or separately will be used. Pilot data show that it is possible to integrate intensive, high-dosage, targeted hand therapy into the routine of an acute rehabilitation setting. The study integrates the behavioral, the kinematic/kinetic and neurophysiological aspects of recovery to determine: 1) whether early intensive training focusing on the hand will result in a more functional hemiparetic arm; (2) whether it is necessary to initiate intensive hand therapy during the very early inpatient rehabilitation phase or will comparable outcomes be achieved if the therapy is initiated right after discharge, in the outpatient period; and 3) whether the effect of the early intervention observed at 6 months post stroke can be predicted by the cortical reorganization evaluated immediately prior to the therapy. This study will fill critical gaps in the literature and make a significant advancement in the investigation of putative interventions for recovery of hand function in patients post-stroke.
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