High density electromyography data of normally limbed and transradial amputee subjects for multifunction prosthetic control
High density electromyography data of normally limbed and transradial amputee subjects for multifunction prosthetic control
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DOI：
10.1016/j.jelekin.2011.12.012
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发表时间：
2012-06-01
影响因子：
2.5
通讯作者：
Kuruganti, Usha
中科院分区：
文献类型：
--
作者：
Daley, Heather;Englehart, Kevin;Kuruganti, Usha
基于模式识别的动力上肢肌电假肢控制提供了一种从可用肌肉中提取更多信息的方法。通过识别跨多个肌肉部位的可重复的肌肉活动模式，而不是依赖于独立的肌电图信号，可以提供更自然、更可靠的肌电假体控制。本研究的目的是：(1)确定参与者是否能够可靠地执行与多次手腕和手部运动相关的独特肌肉激活模式；(2)表明高密度肌电图可以单独应用于确定临床可接受的电极数量（最多八个）的电极位置，从而可靠地对经桡骨截肢者的多次手腕和手部运动进行分类。以8名四肢正常的受试者（5名女性，3名男性）和4名经桡骨截肢的受试者（2名创伤性和先天性）为研究对象，研究了模式识别控制系统的分类准确性。研究发现，正常肢体受试者（10-13个任务）和截肢者（4-6个任务）的任务分类准确率较高（85-98%）。在健康受试者中，将电极数量减少到8个，当电极放置在最佳位置时，不会显著影响准确性，但当电极均匀分布时，会显著降低准确性。在截肢受试者中，将电极数量减少到4个并不影响分类准确性或高精度任务的数量，而与剩余电极是否均匀分布或最佳放置无关。健康受试者的研究结果表明，高密度肌电图测试是确定模式识别控制的最佳电极位置的有用工具，但其在截肢者中的应用仍有待证实。临床医生将能够选择为分类提供最重要信息的电极位置，而不仅仅是识别肌电图活动强烈的电极位置。(C) 2012 Elsevier Ltd.版权所有。
Pattern recognition based control of powered upper limb myoelectric prostheses offers a means of extracting more information from the available muscles than conventional methods. By identifying repeatable patterns of muscle activity across multiple muscle sites rather than relying on independent EMG signals it is possible to provide more natural, reliable control of myoelectric prostheses. The purposes of this study were to (1) determine if participants can perform distinctive muscle activation patterns associated with multiple wrist and hand movements reliably and (2) to show that high density EMG can be applied individually to determine the electrode location of a clinically acceptable number of electrodes (maximally eight) to classify multiple wrist and hand movements reliably in transradial amputees. Eight normally limbed subjects (five female, three male) and four transradial amputee subjects (two traumatic and congenital) subjects participated in this study, which examined the classification accuracies of a pattern recognition control system. It was found that tasks could be classified with high accuracy (85-98%) with normally limbed subjects (10-13 tasks) and with amputees (4-6) tasks. In healthy subjects, reducing the number of electrodes to eight did not affect accuracy significantly when those electrodes were optimally placed, but did reduce accuracy significantly when those electrodes were distributed evenly. In the amputee subjects, reducing the number of electrodes up to 4 did not affect classification accuracy or the number of tasks with high accuracy, independent of whether those remaining electrodes were evenly distributed or optimally placed. The findings in healthy subjects suggest that high density EMG testing is a useful tool to identify optimal electrode sites for pattern recognition control, but its use in amputees still has to be proven. Instead of just identifying the electrode sites where EMG activity is strong, clinicians will be able to choose the electrode sites that provide the most important information for classification. (C) 2012 Elsevier Ltd. All rights reserved.