Assessment of Myoelectric Controller Performance and Kinematic Behavior of a Novel Soft Synergy-Inspired Robotic Hand for Prosthetic Applications.
Assessment of Myoelectric Controller Performance and Kinematic Behavior of a Novel Soft Synergy-Inspired Robotic Hand for Prosthetic Applications.
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DOI：
10.3389/fnbot.2016.00011
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发表时间：
2016
影响因子：
3.1
通讯作者：
Santello M
中科院分区：
文献类型：
--
作者：
Fani S;Bianchi M;Jain S;Pimenta Neto JS;Boege S;Grioli G;Bicchi A;Santello M
肌电假肢可以显着推进假肢的最新技术水平，因为它们可以用来控制机电设备通过肌肉活动的方式，模仿如何使用的对象来激活他们的肌肉之前肢体损失。然而，调查表明，对终端设备的功能不满意是广泛放弃假肢的原因。我们认为，提高假肢设备的可接受性的一个关键因素是实现假肢运动的人类相似性，这是社会和人机交互研究所追求的目标。因此，为了减少早期放弃的终端设备，我们建议，控制器的设计，以确保有效的任务完成在一个自然的方式。在这项工作中，我们分析并比较了三种基于表面肌电信号的肌电控制器算法的性能，以控制欠驱动和多自由度假手SoftHand Pro。本研究的目的是确定最能模仿原生手部运动的肌电算法。作为初步步骤，我们首先量化了SoftHand Pro手指运动的可重复性，并从两对肌肉中确定了具有最高信噪比的健全个体的肌电记录部位，即，指浅屈肌/指总伸肌和桡侧腕屈肌/尺侧腕伸肌。然后要求身体健全的志愿者执行伸手抓握运动，同时记录来自指浅屈肌/指总伸肌的肌电图信号，因为这被确定为具有高信噪比和直观控制的肌肉对。随后，我们测试了三个肌电控制器，将肌电图信号映射到SoftHand Pro的位置。我们发现，差分肌电图位置映射确保了最高的一致性与手部动作。我们的研究结果是迈向更有效和直观的控制肌电假肢的第一步。
Myoelectric artificial limbs can significantly advance the state of the art in prosthetics, since they can be used to control mechatronic devices through muscular activity in a way that mimics how the subjects used to activate their muscles before limb loss. However, surveys indicate that dissatisfaction with the functionality of terminal devices underlies the widespread abandonment of prostheses. We believe that one key factor to improve acceptability of prosthetic devices is to attain human likeness of prosthesis movements, a goal which is being pursued by research on social and human–robot interactions. Therefore, to reduce early abandonment of terminal devices, we propose that controllers should be designed so as to ensure effective task accomplishment in a natural fashion. In this work, we have analyzed and compared the performance of three types of myoelectric controller algorithms based on surface electromyography to control an underactuated and multi-degrees of freedom prosthetic hand, the SoftHand Pro. The goal of the present study was to identify the myoelectric algorithm that best mimics the native hand movements. As a preliminary step, we first quantified the repeatability of the SoftHand Pro finger movements and identified the electromyographic recording sites for able-bodied individuals with the highest signal-to-noise ratio from two pairs of muscles, i.e., flexor digitorum superficialis/extensor digitorum communis, and flexor carpi radialis/extensor carpi ulnaris. Able-bodied volunteers were then asked to execute reach-to-grasp movements, while electromyography signals were recorded from flexor digitorum superficialis/extensor digitorum communis as this was identified as the muscle pair characterized by high signal-to-noise ratio and intuitive control. Subsequently, we tested three myoelectric controllers that mapped electromyography signals to position of the SoftHand Pro. We found that a differential electromyography-to-position mapping ensured the highest coherence with hand movements. Our results represent a first step toward a more effective and intuitive control of myoelectric hand prostheses.
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DOI：
10.1302/0301-620x.37b3.506
发表时间：
1955-01-01
影响因子：
--
作者：
BATTYE, CK;NIGHTINGALE, A;WHILLIS, J
通讯作者：
WHILLIS, J
影响因子：
1.5
作者：
Biddiss, Elaine A.;Chau, Tom T.
通讯作者：
Chau, Tom T.
影响因子：
--
作者：
Castellini, Claudio;Gruppioni, Emanuele;Sandini, Giulio
通讯作者：
Sandini, Giulio
影响因子：
3.5
作者：
Dragan, Anca;Srinivasa, Siddhartha
通讯作者：
Srinivasa, Siddhartha
影响因子：
4.6
作者：
Jiang, Ning;Englehart, Kevin B.;Parker, Philip A.
通讯作者：
Parker, Philip A.