中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Hierarchical projected regression for torque of elbow joint using EMG signals

文献类型:会议论文

作者Chen Y(陈洋); Ding QC(丁其川); Zhao XG(赵新刚); Han JD(韩建达)
出版日期2011
会议名称5th International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2011
会议日期May 10-12, 2011
会议地点Wuhan, China
关键词Bioinformatics Biomedical engineering Clustering algorithms Discriminant analysis Muscle Regression analysis Signal processing
中文摘要Predicting Torque by using Electromyography (EMG) signals is a significant problem as long as wearable robots is concerned. In this paper, a coarse-to-fine algorithm, named as Hierarchical Projected Regression, is proposed to estimate the torque of elbow by the surface EMG signals from human's arm. HPR is learned based on a clinical dataset. First, the real torque distribution can be clustered by k-means algorithm. Meanwhile, the EMG signals are divided into multi-clusters corresponding to the partitions of torque dataset. Then, a projected matrix is derived based on the criterion of Linear Discriminant Analysis, by which the low dimensional features are extracted from the original high dimensional EMG. Finally, the process extends to multi-level tree algorithm based on the hierarchical variance reduction of individual torque cluster. The experimental results show the high accuracy and efficiency of this novel method.
收录类别EI
产权排序1
会议主办者IEEE Engineering in Medicine and Biology Society; Wuhan University; Fuzhou University; Nankai University; Overs. Chin. Sch. Environ. Prot. Assoc. (OCSEPA)
会议录5th International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2011
会议录出版者IEEE Computer Society
会议录出版地Piscataway, NJ
语种英语
ISBN号978-1-4244-5089-3
源URL[http://ir.sia.cn/handle/173321/8730]  
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
Chen Y,Ding QC,Zhao XG,et al. Hierarchical projected regression for torque of elbow joint using EMG signals[C]. 见:5th International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2011. Wuhan, China. May 10-12, 2011.

入库方式: OAI收割

来源:沈阳自动化研究所

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