Selection of Optimal EEG Channels for Classification of Signals Correlated with Alcohol Abusers
Many brain events and disorders can be detected by analyzing electroencephalograms (EEGs). Also the availability of quantitative biological markers that are correlated with qualitative psychiatric phenotypes helps us to utilize automated methods to diagnose and classify these phenotypes. One such a psychiatric phenotype is alcoholism. In this study a method to select an optimal subset of EEG channels for the purpose of practical classification of alcohol abusers from normal subjects is proposed, which is based on combination of model-based spectral analysis and correlation matrices. The EEG signals were recorded when the subjects were represented with single trial visual stimuli. The proposed method proved successful in selecting an optimum number of channels which achieved acceptable average classification accuracy.
Channel selection visual evoked potential (VEP) power spectral density (PSD) correlation matrix pattern classification
M.Alavash Shooshtari S.Kamaledin Setarehdan
Biomedical Engineering Department,Science and Research Branch of Islamic Azad University,Tehran, Ira Control and Intelligent Processing Center of Excellence,Faculty of Electrical and Computer Engineeri
国际会议
2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)
北京
英文
1745-1748
2010-08-24（万方平台首次上网日期，不代表论文的发表时间）