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

Sergei Adamovich, Gerard G. Fluet, Alma S. Merians, Abraham Mathai, Qinyin Qiu

Research output: Contribution to journalArticlepeer-review

Abstract

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.

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

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