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Design and Development of a Robotic Platform Based on Virtual Reality Scenarios and Wearable Sensors for Upper Limb Rehabilitation and Visuomotor Coordination

机译:基于虚拟现实场景的机器人平台和可穿戴传感器的机器人平台,用于上肢康复和遮挡传感器

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The work reintegration following shoulder biomechanical overload illness is a multidimensional process, especially for those tasks requiring strength, movement control and arm dexterity. Currently different robotic devices used for upper limb rehabilitation are available on the market, but these devices arc not based on activities focused on the work reintegration. Furthermore, the rehabilitation programmes aimed to the work reintegration are insufficiently focused on the recovery of the necessary skills for the re-employment. In this study the details of the design of an innovative robotic platform integrated with wearable sensors and virtual reality scenarios for upper limbs motor rehabilitation and visuomotor coordination is presented. The design of control strategy will also be introduced. The robotic platform is based on a robotic arm characterized by seven degrees of freedom and by an adaptive control, wearable sensorized insoles, virtual reality (VR) scenarios and the Leap Motion device to track the hand gestures during the rehabilitation training. Future works will address the application of deep learning techniques for the analysis of the acquired big amount of data in order to automatically adapt both the difficulty level of the VR serious games and amount of motor assistance provided by the robot.
机译:肩部生物力学过载疾病后的工作重返社会是一种多维过程,特别是对于需要强度,运动控制和手臂灵活性的任务。目前,用于上肢康复的不同机器人设备可在市场上使用,但这些设备不基于专注于工作重返社会的活动。此外,旨在为工作重返社会的康复计划不够侧重于恢复重新就业的必要技能。在这项研究中,提出了一种与可穿戴传感器的创新机器人平台设计的细节和上肢电机康复和遮挡体协调的虚拟现实场景。还将介绍控制策略的设计。机器人平台是基于机器人臂,其特征在于七个自由度,并通过自适应控制,可佩戴的带传感鞋垫,虚拟现实(VR)的场景和Leap运动装置的康复训练期间跟踪的手势。未来作品将解决深度学习技术的应用,以分析获得的大量数据,以便自动调整VR严重游戏的难度水平和机器人提供的运动援助。

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