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Error Augmentation in Immersive Virtual Reality for Bimanual Upper-Limb Rehabilitation in Individuals With and Without Hemiplegic Cerebral Palsy
IEEE Transactions on Neural Systems and Rehabilitation Engineering ( IF 4.8 ) Pub Date : 2019-12-13 , DOI: 10.1109/tnsre.2019.2959621
Leia C Shum , Bulmaro A Valdes , Nicola J Hodges , H F Machiel Van der Loos

With more readily available commercial immersive virtual reality (VR) technologies, the potential of new feedback strategies as tools to facilitate motor rehabilitation should be investigated. Augmented feedback or error augmentation (EA) can easily be shown in a virtual environment. Here, visual EA provided via immersive VR was tested for its effectiveness to improve bimanual symmetry in a reaching task. A single-session crossover design was used to test two training cases, with or without EA. With EA, the distance between hands in the forward direction was augmented. Participants were recruited from typically developing (TD) populations (n = 12, ages 13–21) and performed in an adapted environment with an initial asymmetry between limbs. Also, five participants with hemiplegic cerebral palsy (CP) (ages 14–21, MACS I-III) completed the study. Among TD participants, a significantly larger change in symmetry in the adapted environment was shown after EA than training without EA (F (1, 10) = 9.64, p = 0.01). Each participant in the CP group also improved more after EA training (8.8–103.7)%, such that they achieved lower symmetry error after training with EA. As participants in both groups adapted more symmetrically with EA, beneficial changes from this training method could be evaluated in future studies for longer-term functional changes.

中文翻译:

具有和不具有偏瘫性脑瘫的个体的上肢双身康复的沉浸式虚拟现实中的错误增强

利用更容易获得的商业沉浸式虚拟现实(VR)技术,应研究将新的反馈策略作为促进运动康复的工具的潜力。增强的反馈或错误增强(EA)可以在虚拟环境中轻松显示。在这里,通过沉浸式VR提供的视觉EA已通过测试其在达成任务中改善双手对称性的有效性。单会话交叉设计用于测试带有或不带有EA的两个训练案例。使用EA时,向前方向上的双手之间的距离增加了。参加者来自典型的发展中(TD)人群(n = 12,年龄13-21岁),并在适应环境中进行,肢体之间最初存在不对称性。此外,五名患有偏瘫性脑瘫(CP)的参与者(14-21岁,MACS I-III)完成了研究。在TD参与者中,与没有EA训练相比,在EA后适应环境中的对称性变化明显更大(F(1,10)= 9.64,p = 0.01)。CP组的每个参与者在进行EA训练后也提高了更多(8.8-103.7)%,从而使他们在EA训练后获得了更低的对称性误差。由于两组参与者都更对称地适应了EA,因此可以在以后的研究中评估这种训练方法的有益变化,以获取长期功能变化。
更新日期:2020-03-04
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