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Classification and Comparative Analysis of Control and Migraine Subjects Using EEG Signals

  • Abhishek Uday Patil
  • Amitabh Dube
  • Rajesh Kumar Jain
  • Ghanshyam Dass Jindal
  • Deepa Madathil
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 862)

Abstract

Migraine is an incapacitating neurovascular disorder that disables the brain by a severe headache and dysfunction of the autonomic nervous system. There is no perfect diagnosis of migraine till date. Migraine diagnosis if replaced by electroencephalogram (EEG) modality could help in the diagnosis of the disease. Recent advances in EEG signal processing have led to multi-resolution, processing, and methods of feature extraction. In this study, a nonlinear parametric method is used to acquire EEG features of and are used for the classification of control and migraine subjects. This EEG classification is carried out by classifiers based on supervised classification methods—backpropagation used in artificial neural network (ANN) and the results are compared with a bilinear supervised classifier support vector machine (SVM). The classification results confirm that the methodology has a potential to classify EEG and can be used to detect EEG of migraine subjects and could thus further result in improved diagnosis of migraine.

Keywords

Electroencephalogram Migraine Classification Entropy SVM 

Notes

Acknowledgements

We would like to show our sincere gratitude toward SMS Medical College, Jaipur where we could actually collect the data and do the processing of the same. We also thank Dr. Amitabh Dube, Mr. Rajesh Sonania, Dr. Rahul Upadhyay, Dr. R. K Jain, Dr. G. D. Jindal, Dr. Abhishek Saini, Dr. Bhupendra Patel, and Dr. Indoria for their assistance with EEG signal acquisition which has a major role in the present study.

Declaration

Our project is funded by a government organization and one of the authors from the government organization is mentioned in the author list. We have taken permissions to use the dataset/images and responsible for any kind of issues in future.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Abhishek Uday Patil
    • 1
  • Amitabh Dube
    • 2
  • Rajesh Kumar Jain
    • 3
  • Ghanshyam Dass Jindal
    • 4
  • Deepa Madathil
    • 1
  1. 1.Department of Sensor & Biomedical TechnologyVellore Institute of Technology (VIT)VelloreIndia
  2. 2.S.M.S. Medical CollegeJaipurIndia
  3. 3.Electronics DivisionBARCMumbaiIndia
  4. 4.Bio-medical EngineeringMGM College of Engineering & TechnologyMumbaiIndia

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