Bill EVR:基于奖励和错误的运动康复学习的虚拟现实框架。

Federico Nardi, Shlomi Haar, A Aldo Faisal
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引用次数: 0

摘要

VR康复目前已是一个成熟的领域,但它通常指基于计算机屏幕的交互式康复活动。近年来,VR耳机的使用越来越多,它可以为现实世界的任务提供身临其境的虚拟环境,但它们缺乏与任务对象的任何物理交互和任何本体感觉反馈。在这里,我们关注的是嵌入式虚拟现实(EVR),这是一个新兴的领域,不仅通过VR耳机的视觉输入,而且触觉反馈都是物理正确的。这是因为受试者与虚拟现实中真实对齐的物理对象进行交互。这项技术使我们能够通过视觉反馈扰动来操纵运动表现和运动学习。Bill EVR是一个允许干预现实世界任务执行的框架,例如打台球,让最终用户参与激发类似生活的情境,以触发运动(再)学习——受试者在虚拟现实中看到并处理现实世界的球杆、台球桌和射击物理球。具体来说,我们开发了我们的平台来隔离和评估运动学习的不同机制,以研究其两个主要组成部分,基于错误和基于奖励的运动适应。这一理解可以为改善神经康复提供见解:事实上,基于奖励的机制被认为会因多巴胺能系统的退化而受损,例如在帕金森病中,而基于错误的机制对于从中风引起的运动错误中恢复至关重要。由于其完全可定制的功能,我们的EVR框架可用于促进几种条件的改善,为基于VR的实现提供了有效的扩展,并构成了一个可以完全根据患者个人需求定制的运动学习工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bill-EVR: An Embodied Virtual Reality Framework for Reward-and-Error-Based Motor Rehab-Learning.

VR rehabilitation is an established field by now, however, it often refers to computer screen-based interactive rehabilitation activities. In recent years, there was an increased use of VR-headsets, which can provide an immersive virtual environment for real-world tasks, but they are lacking any physical interaction with the task objects and any proprioceptive feedback. Here, we focus on Embodied Virtual Reality (EVR), an emerging field where not only the visual input via VR-headset but also the haptic feedback is physically correct. This happens because subjects interact with physical objects that are veridically aligned in Virtual Reality. This technology lets us manipulate motor performance and motor learning through visual feedback perturbations. Bill-EVR is a framework that allows interventions in the performance of real-world tasks, such as playing pool billiard, engaging end-users in motivating life-like situations to trigger motor (re)learning - subjects see in VR and handle the real-world cue stick, the pool table and shoot physical balls. Specifically, we developed our platform to isolate and evaluate different mechanisms of motor learning to investigate its two main components, error-based and reward-based motor adaptation. This understanding can provide insights for improvements in neurorehabilitation: indeed, reward-based mechanisms are putatively impaired by degradation of the dopaminergic system, such as in Parkinson's disease, while error-based mechanisms are essential for recovering from stroke-induced movement errors. Due to its fully customisable features, our EVR framework can be used to facilitate the improvement of several conditions, providing a valid extension of VR-based implementations and constituting a motor learning tool that can be completely tailored to the individual needs of patients.

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