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A Review on Epileptic Seizure Detection and Prediction Using Soft Computing Techniques

  • Satarupa Chakrabarti
  • Aleena SwetapadmaEmail author
  • Prasant Kumar Pattnaik
Chapter
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 374)

Abstract

Epilepsy is a disorder of the central nervous system in which a considerably large number of neurons at a certain instance of time show abnormal electrical activity. Worldwide according to estimation by WHO, roughly 50 million people are affected by epilepsy that includes patients from infants and adolescent to adults. The most common tool that is used for the determining epileptic seizure after its manifestation is the electroencephalogram (EEG). A certain number of changes occur in behavior as well as perception during epilepsy attack that can be noted chronologically. Generally in human being the manifestation of seizure is illustrated by ictal patterns. The onset of seizures are marked by the change in the ictal phase and this change helps in understanding the underlying mechanism of brain during an epileptic attack so that diagnosis and treatment can be bestowed upon the patient. Over the years, research is going in this domain to develop algorithms that can differentiate between seizure and non-seizure phases and develop mechanism that can detect and predict seizure before its onset. In this paper, we have extensively studied different soft computing techniques that have been developed over the years and have addressed the major singular problem of detection and prediction of an epilepsy seizure before its manifestation so that the after effects of the seizure can be minimized. The range of techniques that have been used for this purpose ranges from artificial neural network, support vector machines, adaptive neuro-fuzzy inference system, genetic algorithm and so on. Comparative study of these different soft computing techniques has been studied to obtain an idea about the performance and accuracy of the various methods. The paper also brings forth the practicality of the techniques in real life scenario and identifies the shortcomings as well as determines the area in this domain that holds prospective for future scope of work. Epilepsy research is a fascinating area that comes with numerous potentials for developing automated systems that would open new avenues for treating the patient. Therefore, in this paper a review is done on different soft computing techniques to understand where our research scenario stands and what improvisations can be made that would not only provide better solution and enhance the quality of living of the epilepsy patients but will also find effective answers to the unanswerable questions.

Keywords

EEG Epilepsy Soft computing ANN Fuzzy ANFIS 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Satarupa Chakrabarti
    • 1
  • Aleena Swetapadma
    • 1
    Email author
  • Prasant Kumar Pattnaik
    • 1
  1. 1.School of Computer EngineeringKalinga Institute of Industrial Technology Deemed to be UniversityBhubaneswarIndia

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