Title :
Discrimination of movement imagery EEG based on AR and SVM
Author :
Min Li ; Liu Yang ; Yi Zhang ; Yuan Luo
Author_Institution :
Res. Center of Intell. Syst. & Robot, Chongqing Univ. of Posts & Telecommun., Chongqing, China
Abstract :
In the Brain-computer interface, classification and recognition technology plays an important role, especially the EEG classification and recognition for the movement imagery. In this paper, we use a new type of sensors to collect EEG signals. According to imagine the movement of left or right hand to identify two types of thinking, we proposed a new recognition method based on AR(auto-regressive) and SVM (support vector machine). In the identification process uses different kernel functions to classify comparison test. Compared to the traditional method based on support vector machine and Bayes, the correct rate has been greatly improved, and verifies the effectiveness of the method.
Keywords :
autoregressive processes; brain-computer interfaces; electroencephalography; support vector machines; AR; EEG classification; EEG signals; SVM; auto-regressive process; brain-computer interface; identification process; kernel functions; movement imagery EEG; support vector machine; Accuracy; Brain modeling; Classification algorithms; Electroencephalography; Feature extraction; Kernel; Support vector machines; AR; Brain-computer interface; SVM; movement imagery; recognition;
Conference_Titel :
Automation and Logistics (ICAL), 2011 IEEE International Conference on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4577-0301-0
Electronic_ISBN :
2161-8151
DOI :
10.1109/ICAL.2011.6024741