Realtime Gait Kinematics Classification Using LDA and SVM

摘要：

Gait analysis is an important part of intelligent prosthesis researching. The automatic segmentation and classification of gait kinematic signal could help intelligent prosthesis to get better control performance. Much feature extraction method was employed by researchers, but it could still be improved. The wavelet based filter is adopted in this paper to segment the gait kinematics data, and LDA/SVM is employed to improve the accuracy of recognition. Result shows better performance than that using traditional method.

关键词： Gait kinematics LDA SVM Feature extraction

作者: Shiguang Wen Fei Wang Chengdong Wu

会议类型: 国际会议

会议名称: 2011 China Control and Decision Conference(2011中国控制与决策会议 CCDC)

会议地点: 四川绵阳

会议语种:英文

页码: 592-595

在线出版日期: 2011-05-23（万方平台首次上网日期，不代表论文的发表时间）