Target Achievement Control Test: evaluating real-time myoelectric pattern-recognition control of multifunctional upper-limb prostheses.
Target Achievement Control Test: evaluating real-time myoelectric pattern-recognition control of multifunctional upper-limb prostheses.
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DOI：
10.1682/jrrd.2010.08.0149
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发表时间：
2011
影响因子：
--
通讯作者：
Kuiken TA
中科院分区：
文献类型：
--
作者：
Simon AM;Hargrove LJ;Lock BA;Kuiken TA
尽管基于模式识别的肌电控制系统具有很高的分类精度（~95%），但尚不清楚离线测量如何转化为实时闭环控制。最近，一项实时虚拟测试分析了受试者使用多自由度（DOF）分类器完成运动的情况。虽然该测试提供了实时性能指标，但所需的任务过于简单：运动速度被标准化，而无意的运动被忽略。我们将这些考虑因素纳入了一个新的更具挑战性的虚拟测试，即目标实现控制（TAC）测试。用户尝试使用肌电模式识别将虚拟手臂移动到目标姿势。五名经桡动脉截肢者使用各种分类器（一个与三个DOF）和任务复杂性（每个姿势一个与三个所需运动）进行测试。在单自由度和三自由度分类器之间未发现分类准确性的显著差异（分别为97.2%±2.0%和94.1%± 3.1%）（p=0.14）。使用三自由度分类器，受试者在显著更多的时间内完成的试验减少了31%。与单运动姿势相比，受试者达到三运动姿势所需的时间长3.6±0.8倍。结果强调了闭环性能测量的必要性，并表明TAC测试提供了一个有用的和更具挑战性的工具来测试实时模式识别性能。
Despite high classification accuracies (~95%) of myoelectric control systems based on pattern recognition, it is unclear how well offline measures translate to real-time closed-loop control. Recently, a real-time virtual test analyzed how well subjects completed motions using a multiple–degree of freedom (DOF) classifier. Although this test provided real-time performance metrics, the required task was oversimplified: motion speeds were normalized and unintended movements were ignored. We included these considerations in a new, more challenging virtual test, the Target Achievement Control (TAC) Test. Users attempted to move a virtual arm into a target posture using myoelectric pattern recognition. Five transradial amputees performed the test with various classifier (one vs. three DOF) and task complexities (one vs. three required motions per posture). No significant difference was found in classification accuracy between the one- and three- DOF classifiers (97.2%±2.0% and 94.1%±3.1%, respectively) (p=0.14). Subjects completed 31% fewer trials in significantly more time using the three-DOF classifier. Subjects took 3.6±0.8 times longer to reach a three-motion posture compared to a one-motion posture. The results highlight the need for closed-loop performance measures and demonstrate that the TAC Test provides a useful and more challenging tool to test real-time pattern recognition performance.
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影响因子：
2.2
作者：
Engelhart, K;Hudgins, B;Stevenson, M
通讯作者：
Stevenson, M
影响因子：
4.6
作者：
Hargrove, Levi;Zhou, Ping;Kuiken, Todd A.
通讯作者：
Kuiken, Todd A.
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.
影响因子：
4.6
作者：
Jiang, Ning;Englehart, Kevin B.;Parker, Philip A.
通讯作者：
Parker, Philip A.
DOI：
10.1016/j.pmr.2005.10.001
发表时间：
2006-02-01
影响因子：
1.7
作者：
Kuiken, Todd
通讯作者：
Kuiken, Todd