epsilon-SVR-based Estimation for the Motion Trajectory of HumanLower Limb Using Acceleration Signals
Dongxu Zhang; Zeng-Guang Hou; Long Cheng; Guibin Bian; Xiaoliang Xie; Liang Peng
2016
会议名称 IEEE International Conference on Information and Automation (ICIA)
会议日期 AUG 01-03, 2016
会议地点Ningbo
会议举办国China
摘要Active training mode has good clinical effect for patients who need lower limb rehabilitation, and estimation for the motion trajectory of human lower limb is one of the most important and fundamental work for active training. In this study, a novel estimation method is proposed based on e-support vector regression (epsilon-SVR) using acceleration signals of lower limb. Firstly, some qualitative variation regularities between acceleration signals of lower limb superficial muscle group and angle values of hip, knee and ankle joints were obtained through the preliminary analysis of the data, which were acquired in the experiments designed and performed in different motion trajectories that were cycling, walk and pedaling. Then, according to the regularities, the input vectors and the output vectors of epsilon-SVR were determined for the estimation model. After that, experimental data were divided into training data and test data. The estimation model was built based on epsilon-SVR using training data. At last, the estimation model was verified through the test data. The results were that the absolute mean error between predicted values and measured values were respectively 6.26 degrees,4.86 degrees and 5.75 degrees for three kinds of motion trajectories that were cycling, walk and pedaling. The effectiveness and applicability of the estimation model for active training of rehabilitation were confirmed.
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/23131
专题复杂系统管理与控制国家重点实验室_先进机器人
推荐引用方式
GB/T 7714
Dongxu Zhang,Zeng-Guang Hou,Long Cheng,et al. epsilon-SVR-based Estimation for the Motion Trajectory of HumanLower Limb Using Acceleration Signals[C],2016.
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