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一种用于经桡骨截肢者的肌电姿势控制算法:对临床准备情况的考量。

A Myoelectric Postural Control Algorithm for Persons With Transradial Amputations: A Consideration of Clinical Readiness.

作者信息

Segil Jacob L, Kaliki Rahul, Uellendahl Jack, Ff Weir Richard F

机构信息

Rocky Mountain Regional VA Medical Center and the Engineering Plus Program at the University of Colorado Boulder, Boulder CO, 80304.

Infinite Biomedical Technologies, Baltimore, MD 21202.

出版信息

IEEE Robot Autom Mag. 2020 Mar;27(1):77-86. doi: 10.1109/mra.2019.2949688. Epub 2019 Nov 20.

DOI:10.1109/mra.2019.2949688
PMID:32494115
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7269158/
Abstract

BACKGROUND

The bottleneck in upper limb prosthetic design is the myoelectric control algorithm. Here we studied the clinical readiness of the myoelectric postural control algorithm in a laboratory setting with two trans-radial amputees using a commercially available prosthetic limb system.

TECHNIQUE

The postural control algorithm was integrated into prosthetic limb systems using standard of care components. A comparison between a commercial state of the art system (the i-limb revolution state-based myoelectric controller) and the postural controller was performed with two people with trans-radial amputation using a self-contained prosthesis system.

DISCUSSION

The performance using the i-limb revolution state-based controller versus the postural controller was mixed based on the Southampton Hand Assessment Procedure. The SHAP scores indicate that the postural controller with i-limb revolution provided an average of 66% of hand function compared to an intact limb. Future work will study the advantages of the postural control algorithm in everyday use.

摘要

背景

上肢假肢设计的瓶颈在于肌电控制算法。在此,我们在实验室环境中,使用市售假肢系统,对两名经桡骨截肢者研究了肌电姿势控制算法的临床适用性。

技术

姿势控制算法通过护理标准组件集成到假肢系统中。使用独立假肢系统,对两名经桡骨截肢者进行了商业先进系统(i-limb revolution基于状态的肌电控制器)与姿势控制器之间的比较。

讨论

根据南安普顿手功能评估程序,使用i-limb revolution基于状态的控制器与姿势控制器的性能有好有坏。南安普顿手功能评估程序(SHAP)评分表明,与健全肢体相比,配备i-limb revolution的姿势控制器平均提供了66%的手部功能。未来的工作将研究姿势控制算法在日常使用中的优势。

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本文引用的文献

1
Myoelectric control with abstract decoders.肌电控制与抽象解码器。
J Neural Eng. 2018 Oct;15(5):056003. doi: 10.1088/1741-2552/aacbfe. Epub 2018 Jun 12.
2
Myoelectric Pattern Recognition Outperforms Direct Control for Transhumeral Amputees with Targeted Muscle Reinnervation: A Randomized Clinical Trial.肌电模式识别优于靶向肌肉神经再支配的转肩截肢患者的直接控制:一项随机临床试验。
Sci Rep. 2017 Oct 23;7(1):13840. doi: 10.1038/s41598-017-14386-w.
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Limb Position Tolerant Pattern Recognition for Myoelectric Prosthesis Control with Adaptive Sparse Representations From Extreme Learning.基于极限学习的自适应稀疏表示的肌电假肢控制的肢体位置容差模式识别
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Functional Assessment of a Myoelectric Postural Controller and Multi-Functional Prosthetic Hand by Persons With Trans-Radial Limb Loss.经桡骨截肢者对肌电姿势控制器和多功能假手的功能评估
IEEE Trans Neural Syst Rehabil Eng. 2017 Jun;25(6):618-627. doi: 10.1109/TNSRE.2016.2586846. Epub 2016 Jun 30.
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Novel postural control algorithm for control of multifunctional myoelectric prosthetic hands.用于控制多功能肌电假手的新型姿势控制算法。
J Rehabil Res Dev. 2015;52(4):449-66. doi: 10.1682/JRRD.2014.05.0134.
6
Comparative study of state-of-the-art myoelectric controllers for multigrasp prosthetic hands.用于多抓握假手的先进肌电控制器的比较研究。
J Rehabil Res Dev. 2014;51(9):1439-54. doi: 10.1682/JRRD.2014.01.0014.
7
User training for pattern recognition-based myoelectric prostheses: improving phantom limb movement consistency and distinguishability.基于模式识别的肌电假肢用户训练:提高幻肢运动的一致性和可区分性。
IEEE Trans Neural Syst Rehabil Eng. 2014 May;22(3):522-32. doi: 10.1109/TNSRE.2013.2279737. Epub 2013 Oct 7.
8
Mechanical design and performance specifications of anthropomorphic prosthetic hands: a review.拟人化假手的机械设计与性能规格:综述
J Rehabil Res Dev. 2013;50(5):599-618. doi: 10.1682/jrrd.2011.10.0188.
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Abstract and proportional myoelectric control for multi-fingered hand prostheses.多手指手部假肢的抽象与比例肌电控制。
Ann Biomed Eng. 2013 Dec;41(12):2687-98. doi: 10.1007/s10439-013-0876-5. Epub 2013 Aug 9.
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Design and validation of a morphing myoelectric hand posture controller based on principal component analysis of human grasping.基于人手抓握主成分分析的变形肌电手姿态控制器的设计与验证。
IEEE Trans Neural Syst Rehabil Eng. 2014 Mar;22(2):249-57. doi: 10.1109/TNSRE.2013.2260172.