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Motion intention estimation of lower limbs based on sEMG supplement with acceleration signal
Zhao XG(赵新刚); Wang, Rui; Ye D(叶丹)
Department机器人学研究室
Conference Name27th Chinese Control and Decision Conference, CCDC 2015
Conference DateMay 23-25, 2015
Conference PlaceQingdao, China
Source PublicationProceedings of the 2015 27th Chinese Control and Decision Conference, CCDC 2015
PublisherIEEE
Publication PlacePiscataway, NJ, USA
2015
Pages4414-4418
Indexed ByEI ; CPCI(ISTP)
EI Accession number20154401483062
WOS IDWOS:000375232905147
Contribution Rank1
ISBN978-1-4799-7016-2
KeywordSemg Acceleration Signals Motion Intention Estimation Support Vector Machine (Svm)
AbstractLower extremity exoskeleton robot can assist the person standing and walking which are important functions for the disabled or old people who can not make move by themselves. The priority task for exoskeleton robot is to get the movement intentions of wearer. This paper proposes an intention estimation method of lower limbs motion based on multi-types signals including surface electromyography (sEMG) and 3-axis acceleration data. 5 channels sEMG and 3-axis acceleration were collected at the 5 same points from able-bodied and the disabled people respectively. After preprocessed and normalized, different features were extracted from the obtained signals. Support vector machine (SVM) was utilized for motion classification, where features of sEMG signals and acceleration signals were taken as input respectively. We also tested the fusion features of the both signals. Furthermore, compared experiments were carried for the disabled and normal people. Results demonstrated that the proposed method was effective for able-bodied people, while the accuracy of the method for disabled people need to be further improved.
Language英语
Citation statistics
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/17194
Collection机器人学研究室
Affiliation1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
2.College of Information Science and Engineering, Northeastern University, Shenyang, China
Recommended Citation
GB/T 7714
Zhao XG,Wang, Rui,Ye D. Motion intention estimation of lower limbs based on sEMG supplement with acceleration signal[C]. Piscataway, NJ, USA:IEEE,2015:4414-4418.
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