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  • 标题:CLASSIFICATION OF BRAINWAVE USING DATA MINING IN PRODUCING AN EMOTIONAL MODEL
  • 本地全文:下载
  • 作者:NURSHUHADA MAHFUZ ; WAIDAH ISMAIL ; ZALISHAM JALI
  • 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
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