The complexity of sensorimotor control required for hand function as well as the wide range of recovery of manipulative abilities makes rehabilitation of the hand most challenging. Our past work has shown that training in a virtual environment (VE) using repetitive, adaptive algorithms has the potential to be an effective rehabilitation medium to facilitate motor recovery of hand function. These findings are in accordance with current neuroscience literature in animals and motor control literature in humans. We are now in a position to refine and optimize elements of the training paradigms to enhance neuroplasticity.
Our first aim tests if and how competition among body parts for neural representations stifles functional gains from different types of training regimens.
The second aim tests the functional benefits of unilateral versus bilateral training regimens.
The third aim tests whether functional improvements gained from training in a virtual environment transfer to other (untrained) skills in the real world.

Public Health Relevance

The potential benefit of this study will be to provide more targeted therapeutic interventions so as to maximize recovery of function in the hemiplegic hand of patients who have had a stroke. The study will use interactive virtual reality-based gaming simulations to encourage the intensity of practice needed for motor recovery. Information gained will help to uncover the potential benefits of these interventions on facilitating recovery of hand function.

National Institute of Health (NIH)
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Research Project (R01)
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Musculoskeletal Rehabilitation Sciences Study Section (MRS)
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Shinowara, Nancy
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Rutgers University
Biomedical Engineering
Schools of Engineering
United States
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Saleh, Soha; Adamovich, Sergei V; Tunik, Eugene (2014) Mirrored feedback in chronic stroke: recruitment and effective connectivity of ipsilesional sensorimotor networks. Neurorehabil Neural Repair 28:344-54
Fluet, Gerard G; Merians, Alma S; Qiu, Qinyin et al. (2014) Comparing integrated training of the hand and arm with isolated training of the same effectors in persons with stroke using haptically rendered virtual environments, a randomized clinical trial. J Neuroeng Rehabil 11:126
Tunik, Eugene; Saleh, Soha; Adamovich, Sergei V (2013) Visuomotor discordance during visually-guided hand movement in virtual reality modulates sensorimotor cortical activity in healthy and hemiparetic subjects. IEEE Trans Neural Syst Rehabil Eng 21:198-207
Merians, Alma S; Fluet, Gerard G; Qiu, Qinyin et al. (2011) Learning in a virtual environment using haptic systems for movement re-education: can this medium be used for remodeling other behaviors and actions? J Diabetes Sci Technol 5:301-8
Merians, Alma S; Fluet, Gerard G; Qiu, Qinyin et al. (2011) Robotically facilitated virtual rehabilitation of arm transport integrated with finger movement in persons with hemiparesis. J Neuroeng Rehabil 8:27
Fluet, Gerard G; Qiu, Qinyin; Kelly, Donna et al. (2010) Interfacing a haptic robotic system with complex virtual environments to treat impaired upper extremity motor function in children with cerebral palsy. Dev Neurorehabil 13:335-45
Adamovich, Sergei V; Fluet, Gerard G; Tunik, Eugene et al. (2009) Sensorimotor training in virtual reality: a review. NeuroRehabilitation 25:29-44
Adamovich, Sergei V; Fluet, Gerard G; Mathai, Abraham et al. (2009) Design of a complex virtual reality simulation to train finger motion for persons with hemiparesis: a proof of concept study. J Neuroeng Rehabil 6:28
Tunik, Eugene; Adamovich, Sergei V (2009) Remapping in the ipsilesional motor cortex after VR-based training: a pilot fMRI study. Conf Proc IEEE Eng Med Biol Soc 2009:1139-42
Qiu, Qinyin; Ramirez, Diego A; Saleh, Soha et al. (2009) The New Jersey Institute of Technology Robot-Assisted Virtual Rehabilitation (NJIT-RAVR) system for children with cerebral palsy: a feasibility study. J Neuroeng Rehabil 6:40

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