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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)
作者部门机器人学研究室
会议名称27th Chinese Control and Decision Conference, CCDC 2015
会议日期May 23-25, 2015
会议地点Qingdao, China
会议录名称Proceedings of the 2015 27th Chinese Control and Decision Conference, CCDC 2015
出版者IEEE
出版地Piscataway, NJ, USA
2015
页码4414-4418
收录类别EI ; CPCI(ISTP)
EI收录号20154401483062
WOS记录号WOS:000375232905147
产权排序1
ISBN号978-1-4799-7016-2
关键词Semg Acceleration Signals Motion Intention Estimation Support Vector Machine (Svm)
摘要Lower 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.
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/173321/17194
专题机器人学研究室
作者单位1.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
推荐引用方式
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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