文章基本信息

标题：CLASSIFICATION OF BRAINWAVE USING DATA MINING IN PRODUCING AN EMOTIONAL MODEL
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作者：NURSHUHADA MAHFUZ ; WAIDAH ISMAIL ; ZALISHAM JALI 等
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2015
卷号：75
期号：2
出版社：Journal of Theoretical and Applied
摘要：In this paper, classification of brainwave using real world data from Parkinson�s patients is presented. Emotional model is produced from the classification of brainwave. Electroencephalograph (EEG) signal is recorded on eleven Parkinson�s patients. This paper aim to find the �best� classification for the emotional model in brainwave patterns for the Parkinson�s disease. The work performed based on the two method phases which are using the raw data and pre-processing data. In each of the method, we performed for steps in the sum of the hertz and divided by total hertz. In the pre-processing data we are using statistic mean and standard deviation. We used WEKA Application for the classification with 11 fold validation. As a results, implecart from the classification tree performed the �best� classification for the emotional model for Parkinson Patients. The Simplecart classification result is 84.42% accuracy.
关键词：Classification; Brainwave; Emotional Model; Parkinson Patients