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首页> 外文期刊>Journal of assistive technologies. >Close range depth sensing cameras for virtual reality based hand rehabilitation
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Close range depth sensing cameras for virtual reality based hand rehabilitation

机译:近距离深度感应相机,用于基于虚拟现实的手部康复

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Purpose - The Leap Motion represents a new generation of depth sensing cameras designed for close range tracking of hands and fingers, operating with minimal latency and high spatial precision (0.01 mm). The purpose of this paper is to develop virtual reality (VR) simulations of three well-known hand-based rehabilitation tasks using a commercial game engine and utilising a Leap camera as the primary mode of interaction. The authors present results from an initial evaluation by professional clinicians of these VR simulations for use in their hand and finger physical therapy practice. Design/methodology/approach - A cross-disciplinary team of researchers collaborated with a local software company to create three dimension interactive simulations of three hand focused rehabilitation tasks: Cotton Balls, Stacking Blocks, and the Nine Hole Peg Test. These simulations were presented to a group of eight physiotherapists and occupational therapists (n = 8) based in the Regional Acquired Brain Injury Unit, Belfast Health, and Social Care Trust for evaluation. After induction, the clinicians attempted the tasks presented and provided feedback by filling out a questionnaire. Findings - Results from questionnaires (using a Likert scale 1-7, where 1 was the most favourable response) revealed a positive response to the simulations with an overall mean score across all questions equal to 2.59. Clinicians indicated that the system contained tasks that were easy to understand (mean score 1.88), and though it took several attempts to become competent, they predicted that they would improve with practice (mean score 2.25). In general, clinicians thought the prototypes provided a good illustration of the tasks required in their practice (mean score 2.38) and that patients would likely be motivated to use the system (mean score 2.38), especially young patients (mean score 1.63), and in the home environment (mean score 2.5). Originality/value- Cameras offer an unobtrusive and low maintenance approach to tracking user motion in VR therapy in comparison to methods based on wearable technologies. This paper presents positive results from an evaluation of the new Leap Motion camera for input control of VR simulations or games. This mode of interaction provides a low cost, easy to use, high-resolution system for tracking fingers and hands, and has great potential for home-based physical therapies, particularly for young people.
机译:目的-Leap Motion代表了新一代的深度感测摄像头,专为近距离跟踪手和手指而设计,以最小的延迟和高空间精度(0.01 mm)进行操作。本文的目的是使用商业游戏引擎并使用Leap相机作为主要的交互模式,开发三种已知的基于手的康复任务的虚拟现实(VR)仿真。作者介绍了专业临床医生对这些VR模拟的初步评估结果,并将其用于手和手指的物理治疗实践。设计/方法/方法-一个跨学科的研究人员团队与一家本地软件公司合作,创建了针对三个手部康复任务的三维交互模拟:棉花球,堆叠块和九孔钉测试。将这些模拟结果介绍给了八名物理治疗师和职业治疗师(n = 8),他们来自地区性后天性脑损伤科,贝尔法斯特卫生和社会关怀基金会。入职后,临床医生尝试完成提出的任务并通过填写调查表提供反馈。结果-问卷调查的结果(使用李克特量表1-7,其中1是最满意的回答)显示出对模拟的积极响应,所有问题的平均总分等于2.59。临床医生指出,该系统包含易于理解的任务(平均得分1.88),尽管经过几次尝试才能胜任,但他们预测,随着实践的发展,这些任务将有所改善(平均得分2.25)。一般而言,临床医生认为原型可以很好地说明其实践所需的任务(平均得分2.38),并且可能会激发患者使用该系统(平均得分2.38),尤其是年轻患者(平均得分1.63),并且在家庭环境中(平均得分2.5)。独创性/价值-与基于可穿戴技术的方法相比,相机提供了一种引人注目的且维护成本低的方法来跟踪VR治疗中的用户运动。本文从对用于虚拟现实模拟或游戏输入控制的新型Leap Motion摄像机的评估中得出了积极的结果。这种交互方式提供了一种低成本,易于使用的高分辨率系统来跟踪手指和手,并且对于家庭式物理疗法(特别是对于年轻人)具有很大的潜力。

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