title: Innovative approaches to the rehabilitation of upper extremity hemiparesis using virtual environments.
abstract: OBJECTIVE
  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.
  
  
  CONCLUSIONS
  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.
authors.forename: A S
authors.initials: AS
authors.lastname: Merians
authors.forename: E
authors.initials: E
authors.lastname: Tunik
authors.forename: G G
authors.initials: GG
authors.lastname: Fluet
authors.forename: Q
authors.initials: Q
authors.lastname: Qiu
authors.forename: S V
authors.initials: SV
authors.lastname: Adamovich
mesh_terms: D000328:Adult; D003198:Computer Simulation; D004867:Equipment Design; D005081:Exercise Therapy / Q000295:instrumentation*; D005240:Feasibility Studies; D006801:Humans; D008279:Magnetic Resonance Imaging; D008875:Middle Aged; D010291:Paresis / Q000503:physiopathology / Q000534:rehabilitation*; D020127:Recovery of Function / Q000502:physiology; D020521:Stroke / Q000503:physiopathology; D000071939:Stroke Rehabilitation; D050781:Transcranial Magnetic Stimulation; D016896:Treatment Outcome; D034941:Upper Extremity / Q000503:physiopathology*; D014584:User-Computer Interface