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Innovative approaches to the rehabilitation of upper extremity hemiparesis using virtual environments.

Alma S. Merians, Eugene Tunik, Gerard G. Fluet, Qinyin Qiu, S. V. Adamovich

发表年份
2009
引用次数
67

摘要

AIM: Upper-extremity interventions for hemiparesis are a challenging aspect of stroke rehabilitation. Purpose of this paper is to report the feasibility of using virtual environments (VEs) in combination with robotics to assist recovery of hand-arm function and to present preliminary data demonstrating the potential of using sensory manipulations in VE to drive activation in targeted neural regions. METHODS: We trained 8 subjects for 8 three hour sessions using a library of complex VE's integrated with robots, comparing training arm and hand separately to training arm and hand together. Instrumented gloves and hand exoskeleton were used for hand tracking and haptic effects. Haptic Master robotic arm was used for arm tracking and generating three-dimensional haptic VEs. To investigate the use of manipulations in VE to drive neural activations, we created a "virtual mirror" that subjects used while performing a unimanual task. Cortical activation was measured with functional MRI (fMRI) and transcranial magnetic stimulation. RESULTS: Both groups showed improvement in kinematics and measures of real-world function. The group trained using their arm and hand together showed greater improvement. In a stroke subject, fMRI data suggested virtual mirror feedback could activate the sensorimotor cortex contralateral to the reflected hand (ipsilateral to the moving hand) thus recruiting the lesioned hemisphere. CONCLUSION: Gaming simulations interfaced with robotic devices provide a training medium that can modify movement patterns. In addition to showing that our VE therapies can optimize behavioral performance, we show preliminary evidence to support the potential of using specific sensory manipulations to selectively recruit targeted neural circuits.

关键词

HemiparesisRehabilitationPhysical medicine and rehabilitationMedicineTranscranial magnetic stimulationHaptic technologyRobotic armMotor learningKinematicsRobotics

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