Measurements by A LEAP-Based Virtual Glove for the Hand Rehabilitation.

Measurements by A LEAP-Based Virtual Glove for the Hand Rehabilitation.
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DOI:
10.3390/s18030834
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发表时间:
2018-03-10
期刊:
Sensors (Basel, Switzerland)
影响因子:
--
通讯作者:
Spezialetti M
Spezialetti M
中科院分区:
其他
文献类型:
--
作者:
Placidi G;Cinque L;Polsinelli M;Spezialetti M

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手康复是中风或手术后的基础。传统的康复需要治疗师,这意味着高成本,患者的压力,以及对治疗效果的主观评价。基于机械和跟踪手套的替代方法在虚拟现实(VR)环境中使用时可能非常有效。机械设备通常是昂贵的、笨重的、患者特定的和手特定的,而基于跟踪的设备不受这些限制的影响,但是特别是如果基于单个跟踪传感器,则可能遭受闭塞。在本文中,实施多传感器的方法,虚拟手套(VG),同时使用两个正交的LEAP运动控制器的基础上,进行说明。VG的校准和静态定位测量进行了比较,收集与一个准确的空间定位系统。在半径为10 cm、高度为21 cm的圆柱形感兴趣区域中,定位误差小于6 mm。还进行实时手部跟踪测量,分析和报告。手部跟踪测量结果表明,VG实时运行(60 fps),减少了遮挡,并正确管理两个LEAP传感器,从一个传感器跳到另一个传感器时没有任何时间和空间的不连续性。补充材料中还收集了一段演示VG良好性能的视频。结果是有希望的,但必须做进一步的工作,以允许计算由每个手指施加的力时,由机械工具约束(例如,钉板)和用于在抓握这些工具时减少闭塞。虽然VG被提议用于康复目的,但它也可以用于工具和机器人的远程操作以及其他VR应用。
Hand rehabilitation is fundamental after stroke or surgery. Traditional rehabilitation requires a therapist and implies high costs, stress for the patient, and subjective evaluation of the therapy effectiveness. Alternative approaches, based on mechanical and tracking-based gloves, can be really effective when used in virtual reality (VR) environments. Mechanical devices are often expensive, cumbersome, patient specific and hand specific, while tracking-based devices are not affected by these limitations but, especially if based on a single tracking sensor, could suffer from occlusions. In this paper, the implementation of a multi-sensors approach, the Virtual Glove (VG), based on the simultaneous use of two orthogonal LEAP motion controllers, is described. The VG is calibrated and static positioning measurements are compared with those collected with an accurate spatial positioning system. The positioning error is lower than 6 mm in a cylindrical region of interest of radius 10 cm and height 21 cm. Real-time hand tracking measurements are also performed, analysed and reported. Hand tracking measurements show that VG operated in real-time (60 fps), reduced occlusions, and managed two LEAP sensors correctly, without any temporal and spatial discontinuity when skipping from one sensor to the other. A video demonstrating the good performance of VG is also collected and presented in the Supplementary Materials. Results are promising but further work must be done to allow the calculation of the forces exerted by each finger when constrained by mechanical tools (e.g., peg-boards) and for reducing occlusions when grasping these tools. Although the VG is proposed for rehabilitation purposes, it could also be used for tele-operation of tools and robots, and for other VR applications.
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