Title :
Estimation of Brain Activity using Support Vectors Machines
Author :
Seijas, Cesar ; Caralli, Antonino ; Villazana, Sergio
Author_Institution :
Fac. of Eng., Carabobo Univ., Valencia
Abstract :
In this article an application of the support vectors machines (SVM) is presented in the problem of the estimation of brain activity by processing an electroencephalogram (EEG) using SVM. SVM are algorithms of emergent computation that have demonstrated an excellent performance in classification and regression applications; in this article they are used for the estimate of brain activity, analyzing EEG data and detecting brain activity states, or frequencies of the brain waves: alpha, beta, gamma and delta, demonstrating that SVM are a promising alternative in modeling problems in medical area
Keywords :
electroencephalography; medical signal processing; support vector machines; brain activity estimation; electroencephalogram; support vectors machines; Algorithm design and analysis; Brain; Data analysis; Electroencephalography; Frequency estimation; Gamma ray detection; Performance analysis; State estimation; Support vector machine classification; Support vector machines;
Conference_Titel :
Neural Engineering, 2007. CNE '07. 3rd International IEEE/EMBS Conference on
Conference_Location :
Kohala Coast, HI
Print_ISBN :
1-4244-0792-3
Electronic_ISBN :
1-4244-0792-3
DOI :
10.1109/CNE.2007.369744