ECoG Recognition of Motor Imagery Based on SVM Ensemble

摘要：

In this paper, a method of ECoG identification based on SVM Ensemble was proposed to solve the problems of low classification accuracy and weak robustness for ECoG collection during different period of time. Common Spatial Pattern CSP algorithm is used for feature extraction, and Support Vector Machine (SVM) Ensemble is applied for classification of ECoG. Besides, Bagging algorithm and Cross-Validation technique are adopted in individual generation of the SVM Ensemble. The experiment results verified that the accuracy of SVM Ensemble is better than that of single SVM for ECoG collection in different period of time, and the Cross-Validated technique has good performance than that of Bagging. Therefore, SVM Ensemble has stronger robustness and generalization ability compared with individual SVMs, and will improve classification of ECoG signals.

作者: Mingai Li Jinfu Yang Dongmei Hao Songmin Jia

作者单位: Institution of Artificial Intelligence and Robot,Beijing University of Technology,Beijing,100124,Chi College of Life Science and Bio-engineering,Beijing University of Technology,Beijing,100124,China

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Robotics and Biomimetics(2009 IEEE 机器人与仿生技术国际会议 ROBIO 2009)

会议地点: 桂林

会议语种:英文

页码: 1967-1972

在线出版日期: 2009-12-19（万方平台首次上网日期，不代表论文的发表时间）