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Development and Evaluation of a Sensor Glove to Detect Grasp Intention for a Wearable Robotic Hand Exoskeleton

机译:传感器手套的开发和评估,以检测可穿戴机器人手外骨骼的抓握意图

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Restoring hand function in people suffering from neuromotor hand impairment is a crucial step towards regaining independence. Wearable robotic hand orthoses are a promising approach to support that aim by providing grasp assistance in daily life. For successful independent use of such an assistive device, a robust and intuitive method to detect the user’s intention to grasp is crucial. However, current solutions often fail to meet these two requirements. In this work, we present a novel sensor glove to detect the user’s grasp intention for the actuated hand exoskeleton RELab tenoexo by integrating soft flexible sensors into a conventional glove. Through contact detection with the object to grasp, the user input can be directly embedded into the regular movement. Sensor characterization and performance evaluation with three able-bodied subjects have shown that the developed sensor glove works reliably and can accurately detect the user’s grasp intentions with true positive and true negative rates of 93.1% and 97.6%, respectively. A pilot test with a possible end-user with spinal cord injury (SCI) underlined the potential benefits of the approach and helped to identify aspects, that require further improvements. The study demonstrated the general feasibility of this method and paves the way for inherently intuitive intention detection in wearable assistive devices.
机译:恢复患有神经运动性手部损伤的人的手功能是恢复独立性的关键一步。可穿戴的机器人手矫形器是一种有前途的方法,可以通过在日常生活中提供抓握帮助来支持该目标。为了成功地独立使用此类辅助设备,一种可靠且直观的方法来检测用户的抓握意图至关重要。但是,当前的解决方案通常无法满足这两个要求。在这项工作中,我们展示了一种新颖的传感器手套,它通过将柔软的柔性传感器集成到常规手套中,来检测用户对手部外骨骼RELab tenoexo的抓握意图。通过与要抓住的物体进行接触检测,可以将用户输入直接嵌入到常规运动中。通过对三个主体的传感器表征和性能评估,结果表明,开发的传感器手套能够可靠地工作,并且能够以93.1%和97.6%的真实正负率准确检测用户的抓握意图。对可能的脊髓损伤(SCI)最终用户的试点测试强调了该方法的潜在优势,并帮助确定了需要进一步改进的方面。这项研究证明了这种方法的一般可行性,并为可穿戴式辅助设备内在的直观意图检测铺平了道路。

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