ProACT: An Augmented Reality Testbed for Intelligent Prosthetic Arms

IF 4.8 2区 医学 Q2 ENGINEERING, BIOMEDICAL
Shivani Guptasarma;Monroe D. Kennedy
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引用次数: 0

Abstract

Upper-limb amputees face tremendous difficulty in operating dexterous powered prostheses. Previous work has shown that aspects of prosthetic hand, wrist, or elbow control can be improved through “intelligent” control, by combining movement-based or gaze-based intent estimation with low-level robotic autonomy. However, no such solutions exist for whole-arm control. Moreover, hardware platforms for advanced prosthetic control are expensive, and existing simulation platforms are not well-designed for integration with robotics software frameworks. We present the Prosthetic Arm Control Testbed (ProACT), a platform for evaluating intelligent control methods for prosthetic arms in an immersive (Augmented Reality) simulation setting. We demonstrate the use of ProACT through preliminary studies, with non-amputee participants performing an adapted Box-and-Blocks task with and without intent estimation. We further discuss how our observations may inform the design of prosthesis control methods, as well as the design of future studies using the platform. To the best of our knowledge, this constitutes the first study of semi-autonomous control for complex whole-arm prostheses, the first study including sequential task modeling in the context of wearable prosthetic arms, and the first testbed of its kind. Towards the goal of supporting future research in intelligent prosthetics, the system is built upon existing open-source frameworks for robotics, and is available at https://arm.stanford.edu/proact.
ProACT:智能假肢臂增强现实试验台
上肢截肢者在操作灵巧动力假肢时面临着巨大的困难。先前的研究表明,通过“智能”控制,将基于运动或基于注视的意图估计与低水平的机器人自主性相结合,可以改善假手、手腕或肘部的控制。然而,对于整个手臂的控制,不存在这样的解决方案。此外,用于高级假肢控制的硬件平台价格昂贵,现有的仿真平台设计不善,无法与机器人软件框架集成。我们提出了假肢臂控制试验台(ProACT),这是一个在沉浸式(增强现实)仿真环境中评估假肢臂智能控制方法的平台。我们通过初步研究展示了ProACT的使用,非截肢者参与者在有或没有意图估计的情况下执行适应性的盒块任务。我们进一步讨论了我们的观察如何为假体控制方法的设计提供信息,以及使用该平台设计未来的研究。据我们所知,这构成了复杂全臂假肢半自主控制的第一个研究,第一个研究包括可穿戴假肢手臂背景下的顺序任务建模,以及同类的第一个测试平台。为了支持未来智能假肢的研究,该系统建立在现有的机器人开源框架之上,可以在https://arm.stanford.edu/proact上获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
8.60
自引率
8.20%
发文量
479
审稿时长
6-12 weeks
期刊介绍: Rehabilitative and neural aspects of biomedical engineering, including functional electrical stimulation, acoustic dynamics, human performance measurement and analysis, nerve stimulation, electromyography, motor control and stimulation; and hardware and software applications for rehabilitation engineering and assistive devices.
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