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Journal of Medical Systems

, Volume 36, Issue 5, pp 2705–2711 | Cite as

Classification of Juvenile Myoclonic Epilepsy Data Acquired Through Scanning Electromyography with Machine Learning Algorithms

  • Imran Goker
  • Onur OsmanEmail author
  • Serhat Ozekes
  • M. Baris Baslo
  • Mustafa Ertas
  • Yekta Ulgen
Original Paper

Abstract

In this paper, classification of Juvenile Myoclonic Epilepsy (JME) patients and healthy volunteers included into Normal Control (NC) groups was established using Feed-Forward Neural Networks (NN), Support Vector Machines (SVM), Decision Trees (DT), and Naïve Bayes (NB) methods by utilizing the data obtained through the scanning EMG method used in a clinical study. An experimental setup was built for this purpose. 105 motor units were measured. 44 of them belonged to JME group consisting of 9 patients and 61 of them belonged to NC group comprising ten healthy volunteers. k-fold cross validation was applied to train and test the models. ROC curves were drawn for k values of 4, 6, 8 and 10. 100% of detection sensitivity was obtained for DT, NN, and NB classification methods. The lowest FP number, which was obtained by NN, was 5.

Keywords

Scanning electromyography Juvenile myoclonic epilepsy Feed-forward neural networks Support vector machines Decision trees Naïve bayes 

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Imran Goker
    • 1
  • Onur Osman
    • 2
    Email author
  • Serhat Ozekes
    • 3
  • M. Baris Baslo
    • 4
  • Mustafa Ertas
    • 5
  • Yekta Ulgen
    • 6
  1. 1.Faculty of Economics and Administrative Sciences, Department of Management Information SystemsOkan UniversityIstanbulTurkey
  2. 2.Faculty of Engineering and Architecture, Department of Electrical & Electronics EngineeringIstanbul Arel UniversityIstanbulTurkey
  3. 3.Faculty of Engineering and Architecture, Department of Computer EngineeringIstanbul Arel UniversityIstanbulTurkey
  4. 4.Istanbul University Capa Medical FacultyIstanbulTurkey
  5. 5.Anadolu Health CenterIstanbulTurkey
  6. 6.Institute of Biomedical EngineeringBogazici UniversityIstanbulTurkey

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