Two ways to improve myoelectric control for a transhumeral amputee after targeted muscle reinnervation: a case study.
Two ways to improve myoelectric control for a transhumeral amputee after targeted muscle reinnervation: a case study.
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靶向肌肉神经支配后改善经肱骨截肢者肌电控制的两种方法：案例研究
DOI：
10.1186/s12984-018-0376-9
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发表时间：
2018-05-10
影响因子：
5.1
通讯作者：
Xu W
中科院分区：
文献类型：
--
作者：
Xu Y;Zhang D;Wang Y;Feng J;Xu W
背景多功能假体的肌电控制对于因表面肌电信号不足而高位截肢的患者来说是具有挑战性的。一种名为靶向肌肉神经重建(TMR)的外科技术通过提供更多的sEMG控制信号，在肌电控制方面取得了令人印象深刻的改善。在这种情况下，TMR后的sEMG信号会相互耦合，从而限制了传统的基于幅度控制的上肢假肢控制的性能。首先，研究了康复训练对产生独立表面肌电信号的影响。结果表明，经过两个月左右的康复训练后，部分记录到的表面肌电信号仍在靶肌肉上耦合。其次，利用模式识别算法对表面肌电信号进行分类。在第二种方法中，为了进一步提高假肢控制的实时性，采用了基于平均绝对值(MAV)阈值开关的后处理方法。与没有后处理方法的普通公关对照相比，多数票和基于MAV阈值开关的总分分别提高了18%和58%以上。截肢者可以使用基于MAV的标准阈值开关在分配的时间内完成所有任务。截肢者主观上更倾向于基于MAV阈值开关的PR控制，在实验和实际应用中都更准确、更平滑。结论虽然患者康复训练后肌电信号仍然是耦合的，但PR控制和基于MAV阈值开关的应用提高了假体手术的在线性能。试验登记回顾登记http://www.chictr.org.cn/showproj.aspx?proj=22058。
BackgroundMyoelectric control of multifunctional prostheses is challenging for individuals with high-level amputations due to insufficient surface electromyography (sEMG) signals. A surgical technique called targeted muscle reinnervation (TMR) has achieved impressive improvements in myoelectric control by providing more sEMG control signals. In this case, some channels of sEMG signals are coupled after TMR, which limits the performance of conventional amplitude-based control for upper-limb prostheses.MethodsIn this paper, two different ways (training and algorithms) were attempted to solve the problem in a transhumeral amputee after TMR. Firstly, effect of rehabilitation training on generating independent sEMG signals was investigated. The results indicated that some sEMG signals recorded were still coupled over the targeted muscles after rehabilitation training for about two months. Secondly, pattern recognition (PR) algorithm was then applied to classify the sEMG signals. In the second way, to further improve the real-time performance of prosthetic control, a post-processing method named as mean absolute value-based (MAV-based) threshold switches was utilized.ResultsUsing the improved algorithms, substantial improvement was shown in a subset of the modified Action Research Arm Test (ARAT). Compared with common PR control without post-processing method, the total scores increased more than 18% with majority vote and more than 58% with MAV-based threshold switches. The amputee was able to finish all the tasks within the allotted time with the standard MAV-based threshold switches. Subjectively the amputee preferred the PR control with MAV-based threshold switches and reported it to be more accurate and much smoother both in experiment and practical use.ConclusionsAlthough the sEMG signals were still coupled after rehabilitation training on the TMR patient, the online performance of the prosthetic operation was improved through application of PR control with combination of the MAV-based threshold switches.Trial registrationRetrospectively registered http://www.chictr.org.cn/showproj.aspx?proj=22058 .
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影响因子：
4.6
作者：
DOERSCHUK, PC;GUSTAFSON, DE;WILLSKY, AS
通讯作者：
WILLSKY, AS
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：
2.2
作者：
Engelhart, K;Hudgins, B;Stevenson, M
通讯作者：
Stevenson, M
长期开环肌电训练中的用户适应：对假肢控制中肌电图模式识别的影响
影响因子：
4
作者：
He, Jiayuan;Zhang, Dingguo;Zhu, Xiangyang
通讯作者：
Zhu, Xiangyang
影响因子：
120.7
作者：
Kuiken, Todd A.;Li, Guanglin;Lock, Blair A.;Lipschutz, Robert D.;Miller, Laura A.;Stubblefield, Kathy A.;Englehart, Kevin B.
通讯作者：
Englehart, Kevin B.