Epileptic Seizure Classification Using Combined Labels and a Genetic Algorithm-Reference-Cited by-同舟云学术

Epileptic Seizure Classification Using Combined Labels and a Genetic Algorithm

Published:2022-06-14 Issue: Volume: Page:
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Container-title:2022 IEEE 21st Mediterranean Electrotechnical Conference (MELECON)
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Author:

Davidson Scot¹,McCallan Niamh¹,Ng Kok Yew¹,Biglarbeigi Pardis¹,Finlay Dewar¹,Lan Boon Leong²,McLaughlin James¹

Affiliation:

1. NIBEC, Ulster University, Jordanstown Campus, Shore Road,Newtownabbey,UK,BT37 0QB

2. Monash University,School of Engineering,Department of Electrical and Computer Systems Engineering and Advanced Engineering Platform,Bandar Sunway,Malaysia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9842860/9842863/09843099.pdf?arnumber=9843099

Reference21 articles.

1. The TUH EEG CORPUS: A big data resource for automated EEG interpretation

2. The five percent electrode system for high-resolution EEG and ERP measurements

3. The morphology of the spike-wave complex

4. Clinical and electroencephalographic features of simple partial seizures

5. Adult myoclonic epilepsy: A distinct syndrome of idiopathic generalized epilepsy

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1. Epileptic multi-seizure type classification using electroencephalogram signals from the Temple University Hospital Seizure Corpus: A review;Expert Systems with Applications;2023-12

2. Rebalancing Techniques for Asynchronously Distributed EEG Data to Improve Automatic Seizure Type Classification;2023 57th Annual Conference on Information Sciences and Systems (CISS);2023-03-22

3. Seizure Classification Using BERT NLP and a Comparison of Source Isolation Techniques with Two Different Time-Frequency Analysis;2022 IEEE Signal Processing in Medicine and Biology Symposium (SPMB);2022-12-03