Virtual Reality Based on Stereotypical RUPERT for Stroke Functional Rehabilitative Training Scenarios

Xuhui Chen, Chaolin Ma, Shaochun Xu, Jiping He
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引用次数: 1

Abstract

This paper outlines our work in developing a series of game-like VR scenarios to assess and rehabilitate System with 3-D Exercise Machine for Upper Limb, coordination, range of motion and other relevant perceptual motor activities. The novel experiments with a new perturbation paradigm were designed to study the control of hand orientation and arm movement during 3D reach-to-grasp in both human subjects and rhesus monkeys. The experiments captured the signal from the monkey's brain (electrocorticogram, EcoG), and integrated the signals into a DATABASE. Our efforts have focused on building engaging game-based stereoscopic video and audio scenarios that allow clients to participate in perceptual-motor rehabilitation. From the audio and video, the system of DEMO could activate the patient's consciousness to adjust the arm's movement; this depends on the patient self-adjust and self- rehabilitation. Exploratory work using EcoG signal DATABASE to match the motion and the biofeedback model, detect and track 3D body motion, identify body postures and quantify motor performance is also described, this method of biofeedback could extract the subjective desire and promote the effect of the rehabilitative training.
基于刻板印象RUPERT的脑卒中功能康复训练场景虚拟现实
本文概述了我们在开发一系列类似游戏的VR场景来评估和康复系统与3-D运动机上肢,协调,运动范围和其他相关的感知运动活动。设计了一种新的摄动范式实验,研究了人类和恒河猴在三维伸手抓握过程中手部方向和手臂运动的控制。实验捕获了来自猴子大脑的信号(皮质电图,EcoG),并将这些信号整合到数据库中。我们的工作重点是建立引人入胜的基于游戏的立体视频和音频场景,使客户能够参与感知运动康复。从音频和视频来看,DEMO系统可以激活患者的意识来调整手臂的运动;这取决于患者的自我调整和自我康复。利用EcoG信号数据库匹配运动和生物反馈模型,检测和跟踪三维身体运动,识别身体姿势和量化运动表现的探索性工作,这种生物反馈方法可以提取主观愿望,促进康复训练的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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