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dc.contributor.authorNassir, Jana
dc.contributor.authorAlasabi, Majeda
dc.contributor.authorMian Qaisar, Saeed
dc.contributor.authorKhan, Muzammil
dc.date.accessioned2023-04-29T12:14:09Z
dc.date.available2023-04-29T12:14:09Z
dc.date.issued2023-04-05
dc.identifier.doihttps://doi.org/10.1109/ICSCA57840.2023.10087614en_US
dc.identifier.urihttp://hdl.handle.net/20.500.14131/744
dc.description.abstractEpileptic seizures affect millions of people worldwide. Medical treatments exist to help lessen the severity of the damage caused by these seizures. However, people with epilepsy still struggle with unexpected seizures. People who experience epileptic seizures have Electroencephalogram (EEG) signals that show different features in comparison to a healthy brain. In this study, EEG signals are studied to detect the seizures. The incoming signals are denoised by using linear phase filters. In next step these are divided in fix-length segments. Then, each segment is broken down using the Empirical Mode Decomposition (EMD) into Intrinsic Mode Functions (IMFs). For an automatic identification of EEG signals, features are extracted from the collected IMFs and then processed using machine learning techniques. A dataset on epilepsy that is available to the public is used for evaluation. To determine which is the best predictor for the under-consideration dataset, four different classification methods are performed and the results are examined. The system achieves a classification accuracy of 96.70%.en_US
dc.description.sponsorshipEffat Universityen_US
dc.publisherIEEEen_US
dc.subjectMachine Learningen_US
dc.subjectClassificationen_US
dc.subjectEpileptic Seizureen_US
dc.subjectEmpirical Mode Decompositionen_US
dc.subjectElectroencephalogramen_US
dc.titleEpileptic Seizure Detection Using the EEG Signal Empirical Mode Decomposition and Machine Learningen_US
dc.contributor.researcherCollege collaborationen_US
dc.subject.KSAHEALTHen_US
dc.contributor.ugstudent2en_US
dc.source.indexScopusen_US
dc.contributor.departmentElectrical and Computer Engineeringen_US
dc.contributor.firstauthorNassir, Jana
dc.conference.name2023 International Conference on Smart Computing and Application (ICSCA)en_US


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