The Rehabilitation Gaming System: a Review
The Rehabilitation Gaming System: a Review
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DOI：
10.3233/978-1-60750-018-6-65
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发表时间：
2009-01-01
期刊：
影响因子：
--
通讯作者：
Verschure, Paul F. M. J.
中科院分区：
文献类型：
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作者：
Cameirao, Monica S.;Bermudez i Badia, Sergi;Verschure, Paul F. M. J.
在不久的将来，中风将成为疾病和生活质量损失的主要负担之一。然而，我们仍然没有找到可以扩大规模以应对这一挑战的恢复办法。基于虚拟现实的治疗系统是直接解决这一挑战的巨大希望。在这里，我们回顾了基于这项技术的不同方法，它们的假设和临床影响。我们将专注于基于虚拟现实的康复系统，结合联合收割机假设的中风后和神经元机制的恢复，直接旨在解决这一挑战。特别是，我们将分析所谓的康复游戏系统（RGS），该系统提出使用非侵入性多模式刺激来激活完整的神经元系统，为受大脑病变影响的运动区域提供直接刺激。RGS旨在使患者参与适应其表现的任务特定训练场景，允许进行分级难度和复杂性的个性化训练。虽然RGS代表一种通用的康复方法，但它已被专门测试用于中风患者上肢运动缺陷的康复。在本章中，我们回顾了RGS的主要基础和属性，并报告了从健康和中风受试者的研究中提取的主要发现。我们表明，RGS捕捉定性和定量的数据运动缺陷，这是转移之间的真实的和VR任务。此外，我们展示了RGS如何使用详细的评估中风患者的运动学和表现，以个性化的治疗。随后，我们将讨论如何实时生理学可以用来提供额外的措施，以评估任务的难度和主题的参与。最后，我们报告了一项正在进行的急性卒中患者纵向研究的初步结果。
Stroke will become one of the main burdens of disease and loss of quality of life in the near future. However, we still have not found rehabilitation approaches that can scale up so as to face this challenge. Virtual reality based therapy systems are a great promise for directly addressing this challenge. Here we review different approaches that are based on this technology, their assumptions and clinical impact. We will focus on virtual reality based rehabilitation systems that combine hypotheses on the aftermath of stroke and the neuronal mechanisms of recovery that directly aims at addressing this challenge. In particular we will analyze the, so called, Rehabilitation Gaming System (RGS) that proposes the use of non-invasive multi-modal stimulation to activate intact neuronal systems that provide direct stimulation to motor areas affected by brain lesions. The RGS is designed to engage the patients in task specific training scenarios that adapt to their performance, allowing for an individualized training of graded difficulty and complexity. Although RGS stands for a generic rehabilitative approach it has been specifically tested for the rehabilitation of motor deficits of the upper extremities of stroke patients. In this chapter we review the main foundations and properties of the RGS, and report on the major findings extracted from studies with healthy and stroke subjects. We show that the RGS captures qualitative and quantitative data on motor deficits, and that this is transferred between real and VR tasks. Additionally, we show how the RGS uses the detailed assessment of the kinematics and performance of stroke patients to individualize the treatment. Subsequently, we will discuss how real-time physiology can be used to provide additional measures to assess the task difficulty and subject engagement. Finally, we report on preliminary results of an ongoing longitudinal study on acute stroke patients.