Epileptic Seizure Classification Using Combined Labels and a Genetic Algorithm

Scot Davidson, Niamh McCallan, Kok Yew Ng, Pardis Biglarbeigi, Dewar Finlay, Boon Leong Lan, James McLaughlin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

45 Downloads (Pure)


Epilepsy affects 50 million people worldwide and is one of the most common serious neurological disorders. Seizure detection and classification is a valuable tool for diagnosing and maintaining the condition. An automated classification algorithm will allow for accurate diagnosis. Utilising the Temple University Hospital (TUH) Seizure Corpus, six seizure types are compared; absence, complex partial, myoclonic, simple partial, tonic and tonic- clonic models. This study proposes a method that utilises unique features with a novel parallel classifier — Parallel Genetic Naive Bayes (NB) Seizure Classifier (PGNBSC). The PGNBSC algorithm searches through the features and by reclassifying the data each time, the algorithm will create a matrix for optimum search criteria. Ictal states from the EEGs are segmented into 1.8 s windows, where the epochs are then further decomposed into 13 different features from the first intrinsic mode function (IMF). The features are compared using an original NB classifier in the first model. This is improved upon in a second model by using a genetic algorithm (Binary Grey Wolf Optimisation, Option 1) with a NB classifier. The third model uses a combination of the simple partial and complex partial seizures to provide the highest classification accuracy for each of the six seizures amongst the three models (20%, 53%, and 85% for first, second, and third model, respectively).
Original languageEnglish
Title of host publication2022 IEEE 21st Mediterranean Electrotechnical Conference - IEEE MELECON 2022
Number of pages6
ISBN (Electronic)978-1-6654-4280-0
ISBN (Print)978-1-6654-4280-0, 978-1-6654-4281-7
Publication statusPublished online - 14 Jun 2022
Event2022 IEEE 21st Mediterranean Electrotechnical Conference (Melecon) - University of Palermo - Dipartimento di Ingegneria, Palermo, Italy
Duration: 14 Jun 202216 Jun 2022


Conference2022 IEEE 21st Mediterranean Electrotechnical Conference (Melecon)
Abbreviated titleIEEE MELECON 2022
Internet address


  • Electroencephalography (EEG)
  • Epileptic seizure
  • Classification
  • Naive Bayes
  • Genetic algorithm


Dive into the research topics of 'Epileptic Seizure Classification Using Combined Labels and a Genetic Algorithm'. Together they form a unique fingerprint.

Cite this