Recovery of hand function in virtual reality: Training hemiparetic hand and arm together or separately

This study describes a novel robotic system using haptic effects and objects, in rich, three- dimensional virtual environments (VEs) for the sensorimotor training of the hemiparetic hand. This system is used to compare effectiveness of two training paradigms, one using activities that train the hand and arm together (HAT) as a functional unit to training the hand and arm in similar conditions, separately (HAS). Four subjects practiced three hours/day for 8 days using (HAS) robotic simulations. Four subjects practiced same amount of time using HAT simulations. HAT group improved 23% in the Wolf Motor Function Test and 29% in the Jebsen Test of Hand Function, whereas HAS group only improved 14% and 8%. HAT group also demonstrated larger decreases in hand trajectory length in the VE-based training that involved reaching and object placing, indicating improved limb segment coordination, (40% HAT; 19% HAS). Both groups improved the smoothness of robotically measured hand trajectories 56%, suggesting improved motor control. During virtual piano training, subjects showed similar improvements in key press accuracy (17% HAT; 20% HAS) however, the HAT group demonstrated larger improvements in average time needed to press a key (151% HAT; 60% HAS). Our initial findings suggest that training the arm and hand as a unit following stroke may be more effective for improving upper extremity function than training the hand and arm in isolation.

[1]  M. Kossut,et al.  Learning‐induced expansion of cortical maps – what happens to adjacent cortical representations? , 1998, Neuroreport.

[2]  E. Taub,et al.  The EXCITE Trial: Attributes of the Wolf Motor Function Test in Patients with Subacute Stroke , 2005, Neurorehabilitation and neural repair.

[3]  R. H. Jebsen,et al.  An objective and standardized test of hand function. , 1969, Archives of physical medicine and rehabilitation.

[4]  S. Adamovich,et al.  Sensorimotor Training in a Virtual Reality Environment: Does It Improve Functional Recovery Poststroke? , 2006, Neurorehabilitation and neural repair.

[5]  A Ashburn,et al.  Physiotherapy based on the Bobath concept in stroke rehabilitation: a survey within the UK. , 2001, Disability and rehabilitation.

[6]  C. Burgar,et al.  MIME robotic device for upper-limb neurorehabilitation in subacute stroke subjects: A follow-up study. , 2006, Journal of rehabilitation research and development.

[7]  M. Hallett,et al.  Improving hand function in chronic stroke. , 2002, Archives of neurology.

[8]  Michael Recce,et al.  A Virtual RealityBased Exercise System for Hand Rehabilitation Post-Stroke , 2005, Presence: Teleoperators & Virtual Environments.

[9]  Ferdinando A. Mussa-Ivaldi,et al.  Robot-assisted adaptive training: custom force fields for teaching movement patterns , 2004, IEEE Transactions on Biomedical Engineering.

[10]  A. G. Feldman,et al.  The timing of arm-trunk coordination is deficient and vision-dependent in Parkinson's patients during reaching movements , 2000, Experimental Brain Research.

[11]  Douglas C Noll,et al.  Cortical Plasticity During Three-Week Motor Skill Learning , 2004, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[12]  N. Hogan,et al.  Movement Smoothness Changes during Stroke Recovery , 2002, The Journal of Neuroscience.

[13]  S. Small,et al.  Functions of the Mirror Neuron System: Implications for Neurorehabilitation , 2006, Cognitive and behavioral neurology : official journal of the Society for Behavioral and Cognitive Neurology.

[14]  Joanne M Wagner,et al.  Recovery of Grasp versus Reach in People with Hemiparesis Poststroke , 2006, Neurorehabilitation and neural repair.

[15]  R. Nudo,et al.  Neural Substrates for the Effects of Rehabilitative Training on Motor Recovery After Ischemic Infarct , 1996, Science.

[16]  Kathe Coyle A flock of birds , 1995 .