Sensorimotor training in virtual reality: A review

被引:315
作者
Adamovich, Sergei V. [1 ,2 ]
Fluet, Gerard G. [2 ]
Tunik, Eugene [2 ]
Merians, Alma S. [2 ]
机构
[1] New Jersey Inst Technol, Dept Biomed Engn, Motor Control & Rehabil Lab, Newark, NJ 07102 USA
[2] Univ Med & Dent New Jersey, Dept Rehabil & Movement Sci, Newark, NJ 07103 USA
关键词
Virtual reality; virtual environment; sensorimotor training; rehabilitation; PRIMARY MOTOR CORTEX; INDUCED CORTICAL REORGANIZATION; MOVEMENT REPRESENTATIONS; FUNCTIONAL RECOVERY; PHYSICAL-ACTIVITY; EXPOSURE THERAPY; VISUOMOTOR SKILL; FINGER TRACKING; MENTAL PRACTICE; HAND MOVEMENTS;
D O I
10.3233/NRE-2009-0497
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Recent experimental evidence suggests that rapid advancement of virtual reality (VR) technologies has great potential for the development of novel strategies for sensorimotor training in neurorehabilitation. We discuss what the adaptive and engaging virtual environments can provide for massive and intensive sensorimotor stimulation needed to induce brain reorganization. Second, discrepancies between the veridical and virtual feedback can be introduced in VR to facilitate activation of targeted brain networks, which in turn can potentially speed up the recovery process. Here we review the existing experimental evidence regarding the beneficial effects of training in virtual environments on the recovery of function in the areas of gait, upper extremity function and balance, in various patient populations. We also discuss possible mechanisms underlying these effects. We feel that future research in the area of virtual rehabilitation should follow several important paths. Imaging studies to evaluate the effects of sensory manipulation on brain activation patterns and the effect of various training parameters on long term changes in brain function are needed to guide future clinical inquiry. Larger clinical studies are also needed to establish the efficacy of sensorimotor rehabilitation using VR in various clinical populations and most importantly, to identify VR training parameters that are associated with optimal transfer to real-world functional improvements.
引用
收藏
页码:29 / 44
页数:16
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