Methodologies for Epilepsy Detection: Survey and Review

  • Ananya D. Ojha
  • Ananya Navelkar
  • Madhura Gore
  • Dhananjay KalbandeEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1087)


Till date, according to the World Health Organization (WHO), more than 50 million people around the globe are suffering from epilepsy. Epilepsy is a neurological disorder characterized by the onset of intractable seizures. Seizures are the aberrant behaviour of cerebral signals which leaves the patient debilitated. Electroencephalogram (EEG) which measures the brain wave activity and neuro-imaging like CT scan and MRI are usually used for diagnosing epilepsy. Despite the fact that around 12 million Indian citizens suffer from chronic disease, there still exists a huge stigma associated with epilepsy. Social stigma so grave, that in India, there are a considerable number of marriages which are annulled or called off because either of the partners suffers from epilepsy. Compared to a healthy human being, the chances of survival for a person with epilepsy are 1.6–3 times lower. Hence, it calls for more attention to the detection of epilepsy. This paper gives the comparative study of different methodologies implemented so far for epilepsy detection and identifies the existing gaps in these methods.


Epilepsy Neural network Wavelet transform Electroencephalogram (EEG) 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Ananya D. Ojha
    • 1
  • Ananya Navelkar
    • 1
  • Madhura Gore
    • 1
  • Dhananjay Kalbande
    • 2
    Email author
  1. 1.Department of Computer EngineeringSardar Patel Institute of TechnologyAndheri, MumbaiIndia
  2. 2.Department of Information TechnologyG. H. Raisoni College of EngineeringNagpurIndia

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