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A virtual reality-based training system for error-augmented treatment in patients with stroke

机译：基于虚拟现实的中风患者错误增强治疗培训系统

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Stroke is a leading cause of long-term sensorimotor deficits in upper limb function and current upper limb interventions have limited effectiveness. Joint-level augmentation treatment, grounded in referent control theory, prescribes insertion of error at the joint level for inducing a dynamic re-mapping of muscle-leve control mechanisms. We hypothesize that this will lead to an increase in the control range of the joint and consequently to improved performance of voluntary motion. In the current presentation we describe a system harnessing virtual reality developed for upper-limb training based on joint level error augmentation. The system comprises three components, a passive arm rest supporting the arm against gravity, a Kinect motion tracking system, and a virtual-reality training environment. The visualization of the entire arm is a critical system component which should invoke a high degree of presence. For the method to be effective, the participant should accept the visualized arm position as representing his/her actual arm location, despite conflicting input from his/her proprioception. A pilot test is currently under way for assessing the method’s effectiveness.
机译：中风是上肢功能长期感觉运动缺陷的主要原因，目前的上肢干预措施效果有限。以参照控制理论为基础的关节水平增强治疗，规定在关节水平插入错误，以诱导肌肉水平控制机制的动态重新映射。我们假设这将导致关节的控制范围增加，并因此改善自愿运动的表现。在当前的演示中，我们描述了一个基于虚拟现实的系统，该系统是为基于联合误差增强的上肢训练而开发的。该系统包括三个组件：一个被动扶手，用于支撑重力，Kinect运动跟踪系统;以及虚拟现实训练环境。整个手臂的可视化是至关重要的系统组件，应引起高度的关注。为了使该方法有效，参与者应接受可视化的手臂位置来代表他/她的实际手臂位置，尽管他/她的本体感觉输入存在冲突。目前正在进行一项试验性评估，以评估该方法的有效性。

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