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Real-time myoelectric prosthetic-hand control to reject outlier motion interference using one-class classifier
Ding QC(丁其川); Li ZY(李自由); Zhao XG(赵新刚); Xiao, Yongfei; Han JD(韩建达)
作者部门机器人学研究室
会议名称32nd Youth Academic Annual Conference of Chinese Association of Automation, YAC 2017
会议日期May 19-21, 2017
会议地点Hefei, China
会议录名称Proceedings - 2017 32nd Youth Academic Annual Conference of Chinese Association of Automation, YAC 2017
出版者IEEE
出版地New York
2017
页码96-101
收录类别EI ; CPCI(ISTP)
EI收录号20173204024200
WOS记录号WOS:000425862800018
产权排序1
ISBN号9781538629017
关键词Electromyography (Emg) Myoelectric Control Motion Recognition One-class Classification
摘要Electromyography (EMG) has been popularly used as interface command to achieve a natural control for myoelectric prosthetic-hands. Traditional EMG-based recognition methods always only focus on the classification of target motion classes that were defined in the training phase, but have no ability to reject outlier motion interferences that did not present before. In this paper, a hybrid classifier that combines one one-class Gaussian classifiers and a multi-class LDA was constructed to achieve EMG-based motion classification, in which Gaussian classifiers were used to reject outlier interferences, while LDA was used to classify target motion samples. The robust hybrid classifier is easily built and has low run-time complexity. Extensive experiments were conducted to verify the performance of the proposed hybrid classifier, where 91.6% of target motion recognition accuracy and 96.5% of outlier motion rejection accuracy were respectively obtained. Finally, the hybrid classifier was involved to achieve a robust and real-time control of a myoelectric prosthetic-hand.
语种英语
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文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/20821
专题机器人学研究室
通讯作者Ding QC(丁其川)
作者单位1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, 110016, China
2.University of Chinese Academy of Sciences, Beijing, 100049, China
3.Institute of Automation, Shandong Academy of Sciences, Jinan, 250014, China
推荐引用方式
GB/T 7714
Ding QC,Li ZY,Zhao XG,et al. Real-time myoelectric prosthetic-hand control to reject outlier motion interference using one-class classifier[C]. New York:IEEE,2017:96-101.
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