首页> 外文期刊>Neural Systems and Rehabilitation Engineering, IEEE Transactions on >Closed-Loop Control of Grasping With a Myoelectric Hand Prosthesis: Which Are the Relevant Feedback Variables for Force Control?
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Closed-Loop Control of Grasping With a Myoelectric Hand Prosthesis: Which Are the Relevant Feedback Variables for Force Control?

机译:肌电手部假体的闭环控制:力控制的相关反馈变量有哪些?

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摘要

In closed-loop control of grasping by hand prostheses, the feedback information sent to the user is usually the actual controlled variable, i.e., the grasp force. Although this choice is intuitive and logical, the force production is only the last step in the process of grasping. Therefore, this study evaluated the performance in controlling grasp strength using a hand prosthesis operated through a complete grasping sequence while varying the feedback variables (e.g., closing velocity, grasping force), which were provided to the user visually or through vibrotactile stimulation. The experiments were conducted on 13 volunteers who controlled the Otto Bock Sensor Hand Speed prosthesis. Results showed that vibrotactile patterns were able to replace the visual feedback. Interestingly, the experiments demonstrated that direct force feedback was not essential for the control of grasping force. The subjects were indeed able to control the grip strength, predictively, by estimating the grasping force from the prosthesis velocity of closing. Therefore, grasping without explicit force feedback is not completely blind, contrary to what is usually assumed. In our study we analyzed grasping with a specific prosthetic device, but the outcomes are also applicable for other devices, with one or more degrees-of-freedom. The necessary condition is that the electromyography (EMG) signal directly and proportionally controls the velocity/grasp force of the hand, which is a common approach among EMG controlled prosthetic devices. The results provide important indications on the design of closed-loop EMG controlled prosthetic systems.
机译:在手动假体抓紧的闭环控制中,发送给用户的反馈信息通常是实际的控制变量,即抓紧力。尽管这种选择是直观且合乎逻辑的,但力的产生只是抓握过程的最后一步。因此,这项研究评估了通过完整的抓握顺序操作手部假体同时改变视觉或通过触觉刺激提供给用户的反馈变量(例如闭合速度,抓握力)来控制抓握强度的性能。实验是对13名控制Otto Bock传感器手速假体的志愿者进行的。结果表明,震动触觉模式能够代替视觉反馈。有趣的是,实验表明直接的力反馈对于控制抓力并不是必需的。通过从假体闭合速度估算抓握力,受试者确实能够预测性地控制握力。因此,与通常的假设相反,没有明确的力反馈进行抓握并不是完全盲目的。在我们的研究中,我们分析了使用特定假肢设备的抓握,但结果也适用于具有一个或多个自由度的其他假肢设备。必要条件是肌电图(EMG)信号直接且成比例地控制手的速度/抓握力,这是EMG控制的修复设备中的常用方法。研究结果为闭环肌电控制假体的设计提供了重要依据。

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