Motion intention estimation of lower limbs based on sEMG supplement with acceleration signal
文献类型：会议论文
| 作者 | Zhao XG(赵新刚) ; Wang, Rui; Ye D(叶丹)
|
| 出版日期 | 2015 |
| 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 |
| 关键词 | sEMG Acceleration Signals Motion Intention Estimation Support Vector Machine (SVM) |
| 页码 | 4414-4418 |
| 中文摘要 | 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. |
| 收录类别 | EI ; CPCI（ISTP） |
| 产权排序 | 1 |
| 会议录 | Proceedings of the 2015 27th Chinese Control and Decision Conference, CCDC 2015
 |
| 会议录出版者 | IEEE |
| 会议录出版地 | Piscataway, NJ, USA |
| 语种 | 英语 |
| ISBN号 | 978-1-4799-7016-2 |
| WOS记录号 | WOS:000375232905147 |
| 源URL | [http://ir.sia.cn/handle/173321/17194]  |
| 专题 | 沈阳自动化研究所_机器人学研究室 |
| 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]. 见:27th Chinese Control and Decision Conference, CCDC 2015. Qingdao, China. May 23-25, 2015. |
入库方式： OAI收割
来源：沈阳自动化研究所
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