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Comparison of Fuzzy Output Optimization with Expectation Maximization Algorithm and Its Modification for Epilepsy Classification

  • Sunil Kumar Prabhakar
  • Harikumar Rajaguru
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 14)

Abstract

Due to the sudden and hyper excessive electrical discharges occurring in a specific group of cells in brain, a seizure is caused. The occurrence of the seizure can be in different regions of the brain. The person experiences different symptoms depending on the location of the seizure in the brain. So this disorder is usually witnessed and understood by seizures which are recurrent in nature. Due to epilepsy, abnormal behaviour rises such as the muscle movements becomes involuntary, the consciousness level of the patient becomes severely disturbed and it is accompanied by unusual perceptions. It is such a relatively common neurological condition that affects the person irrespective of age and sex. The diagnosis of the epilepsy can be confirmed with the help of Electroencephalography (EEG) signals. The EEG helps to get an accurate observation and description to know what has happened, the current circumstances and its respective severity levels. In this work, the main objective is to optimize the fuzzy output with the help of Expectation Maximization (EM) and Modified Expectation Maximization (MEM) algorithm for the classification and detection of epilepsy risk levels from EEG signals. At the beginning to classify the risk levels of epilepsy from the obtained signals which is based on the extracted parameters like variance, covariance, events, energy, sharp waves, spike waves and peaks, fuzzy techniques are incorporated. The EM and MEM algorithms are then effectively utilized on the initially classified data to get an exact risk level optimization value so that the risk of epilepsy in the patient is characterized easily.

Keywords

Epilepsy EEG EM MEM Fuzzy 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of ECEBannari Amman Institute of TechnologyCoimbatoreIndia

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