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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:基于虚拟现实场景和可穿戴传感器的上肢康复与运动协调机器人平台的设计与开发

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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:肩部生物力学超负荷疾病后的工作重返社会是一个多维过程,尤其是对于那些需要力量,运动控制和手臂灵活性的任务。当前市场上有用于上肢康复的不同机器人设备,但是这些设备并不是基于专注于工作整合的活动。此外,旨在重新融入工作的康复方案没有充分地集中于重新就业所需技能的恢复。在这项研究中,详细介绍了创新型机器人平台的设计细节,该平台集成了可穿戴传感器和虚拟现实场景,用于上肢运动康复和视觉运动协调。控制策略的设计也将被介绍。该机器人平台基于具有七个自由度并具有自适应控制,可穿戴的传感鞋垫,虚拟现实(VR)场景和Leap Motion设备的机器人手臂,该设备可在康复训练过程中跟踪手势。未来的工作将致力于深度学习技术在分析获取的大量数据中的应用,以便自动适应VR严肃游戏的难度水平和机器人提供的运动辅助量。

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