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An user-independent gesture recognition method based on sEMG decomposition
Xiong AB(熊安斌); Zhao XG(赵新刚); Han JD(韩建达); Liu GJ(刘光军); Ding QC(丁其川)
Department机器人学研究室
Conference Name2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Conference DateSeptember 28 - October 2, 2015
Conference PlaceHamburg, Germany
Source Publication2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
PublisherIEEE
Publication PlacePiscataway, NJ, USA
2015
Pages4185-4190
Indexed ByEI ; CPCI(ISTP)
EI Accession number20160801971417
WOS IDWOS:000371885404055
Contribution Rank1
ISBN978-1-4799-9994-1
AbstractsEMG recognition has been used extensively in prosthetic device control, human-assisting manipulators and sign language recognition, etc. However, the sEMG recognition model, trained with one subject's sEMG data, is not applicable to the other subjects, which hinders the practical application of myoelectric interfaces immensely. In this paper, a sEMG recognition method which is applicable to multi-users is proposed. Firstly, single channel sEMG is decomposed into 30 MUAPTs, which includes four steps: two-order differential filter, threshold calculation, spike detection and hierarchical clustering. Secondly, the MUAPTs are updated with the templates orthogonalization; and Deep Boltzman Machine is employed to classify the MUAPTs into five classes corresponding to the predefined five gestures. Six participants participated in this experiment to validate the effectiveness of the proposed method. Results indicated that this method can achieve a mean accuracy of 81.5%.
Language英语
Citation statistics
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/17458
Collection机器人学研究室
Affiliation1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, University of Chinese Academy of Sciences, China
2.Department of Aerospace Engineering, Ryerson University, Toronto, Canada
Recommended Citation
GB/T 7714
Xiong AB,Zhao XG,Han JD,et al. An user-independent gesture recognition method based on sEMG decomposition[C]. Piscataway, NJ, USA:IEEE,2015:4185-4190.
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