Quantitative analysis of the human upper-limp kinematic model for robot-based rehabilitation applications
Quantitative analysis of the human upper-limp kinematic model for robot-based rehabilitation applications
复制标题
基于机器人的康复应用的人体上肢运动学模型的定量分析
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
F. Makedon
中科院分区：
文献类型：
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作者：
Alexandros Lioulemes;Michail Theofanidis;F. Makedon
上肢机器人康复系统应该告知治疗师他们的患者状况。这样的治疗系统的开发必须考虑到与传感器误差相关的现实生活中的不确定性。在我们的论文中，我们描述了一个系统，它由一个跟踪患者上肢运动的深度摄像头和一个用重复练习挑战患者的机器人机械手组成。这项研究的目的是提出一种运动分析系统，通过使用描述人类手臂运动的运动学模型来提高深度相机的读数。在我们目前的实验设置中，我们使用Kinect v2来捕捉一名使用Barrett WAM机器人进行康复练习的参与者。最后，我们给出了来自Kinect v2的独立测量结果、我们的系统的估计运动参数和我们认为是无误差的地面真实仪器VICON之间的数值比较。
Upper-limb robotic rehabilitation systems should inform the therapists for their patients status. Such therapy systems must be developed carefully by taking into consideration real life uncertainties that associate with sensor error. In our paper, we describe a system which is composed of a depth camera that tracks the motion of the patients upper limb, and a robotic manipulator that challenges the patient with repetitive exercises. The goal of this study is to propose a motion analysis system that improves the readings of the depth camera, through the use of a kinematic model that describes the motion of the human arm. In our current experimental set-up we are using the Kinect v2 to capture a participant who performs rehabilitation exercises with the Barrett WAM robotic manipulator. Finally, we provide a numerical comparison among the stand alone measurements from the Kinect v2, the estimated motion parameters of our system and the VICON, which we consider as an error-free ground truth apparatus.