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肌电驱动的共享人与机器人顺应控制在手假体中进行手中物体操作。

EMG-driven shared human-robot compliant control for in-hand object manipulation in hand prostheses.

机构信息

LASA Laboratory, École Polytechnique Fédérale de Lausanne, 1015 Laussane, Switzerland.

Neuro X Institute, École Polytechnique Fédérale de Lausanne, 1202 Genève, Switzerland.

出版信息

J Neural Eng. 2022 Dec 2;19(6). doi: 10.1088/1741-2552/aca35f.

Abstract

. The limited functionality of hand prostheses remains one of the main reasons behind the lack of its wide adoption by amputees. Indeed, while commercial prostheses can perform a reasonable number of grasps, they are often inadequate for manipulating the object once in hand. This lack of dexterity drastically restricts the utility of prosthetic hands. We aim at investigating a novel shared control strategy that combines autonomous control of forces exerted by a robotic hand with electromyographic (EMG) decoding to perform robust in-hand object manipulation.. We conduct a three-day long longitudinal study with eight healthy subjects controlling a 16-degrees-of-freedom robotic hand to insert objects in boxes of various orientations. EMG decoding from forearm muscles enables subjects to move, proportionally and simultaneously, the fingers of the robotic hand. The desired object rotation is inferred using two EMG electrodes placed on the shoulder that record the activity of muscles responsible for elevation and depression. During the object interaction phase, the autonomous controller stabilizes and rotates the object to achieve the desired pose. In this study, we compare an incremental and a proportional shoulder-decoding method in combination with two state machine interfaces offering different levels of assistance.. Results indicate that robotic assistance reduces the number of failures by41%and, when combined with an incremental shoulder EMG decoding, leads to faster task completion time (median = 16.9 s), compared to other control conditions. Training to use the assistive device is fast. After one session of practice, all subjects managed to achieve tasks with50%less failures.. Shared control approaches that give some authority to an autonomous controller on-board the prosthesis are an alternative to control schemes relying on EMG decoding alone. This may improve the dexterity and versatility of robotic prosthetic hands for people with trans-radial amputation. By delegating control of forces to the prosthesis' on-board control, one speeds up reaction time and improves the precision of force control. Such a shared control mechanism may enable amputees to perform fine insertion tasks solely using their prosthetic hands. This may restore some of the functionality of the disabled arm.

摘要

. 手部假肢功能有限仍然是其未能被截肢者广泛采用的主要原因之一。诚然,商业假肢可以执行一定数量的抓握动作,但在放入手中后,往往无法很好地操纵物体。这种缺乏灵活性极大地限制了假肢手的实用性。我们旨在研究一种新的共享控制策略,该策略将机器人手部自主控制施加的力与肌电图(EMG)解码相结合,以实现稳健的手中物体操作。. 我们对八名健康受试者进行了为期三天的纵向研究,他们控制一个具有 16 个自由度的机器人手将物体插入各种方向的盒子中。前臂肌肉的 EMG 解码使受试者能够同时以比例方式移动机器人手的手指。通过放置在肩部记录负责提升和降低的肌肉活动的两个 EMG 电极来推断期望的物体旋转。在物体交互阶段,自主控制器稳定并旋转物体以实现期望的姿势。在这项研究中,我们比较了增量和比例肩部解码方法与两种状态机接口的组合,这两种接口提供了不同程度的辅助。. 结果表明,与其他控制条件相比,机器人辅助可将失败次数减少 41%,并且当与增量肩部 EMG 解码结合使用时,可导致更快的任务完成时间(中位数= 16.9s)。使用辅助设备进行培训很快。经过一次练习,所有受试者都成功地以失败次数减少 50%的方式完成了任务。. 将一些控制权交给假肢上的自主控制器的共享控制方法是一种替代单独依赖 EMG 解码的控制方案。这可能会提高具有桡骨截肢的人的机器人假肢手的灵活性和多功能性。通过将力的控制委托给假肢的板载控制,可以加快反应时间并提高力控制的精度。这种共享控制机制可能使截肢者仅使用其假肢手执行精细的插入任务。这可能会恢复残疾手臂的部分功能。

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