Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Book Chapter Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Impact of Multi-domain Features for EEG Based Epileptic Seizures Classification Subject The topic of the resource Adaptive Boosting; Data Standardization; EEG; Epileptic Seizure; Frequency domain; Gaussian Nae Bayes; Machine Learning; Multi-domain Features; Time domain Description An account of the resource Accurate detection and classification of epileptic seizures play a pivotal role in clinical diagnosis and treatment. This study introduces an innovative approach that leverages multi-domain features extracted from Electroencephalogram (EEG) data in conjunction with Supervised learning classification techniques. Initially, EEG data undergoes preprocessing through data standardization, followed by the extraction of essential features per instance, encompassing combination of Time domain, Frequency domain, and Time-Frequency domain features. These extracted feature combinations are subsequently fed into the machine learning-based boosting classifier Adaptive Boosting (ADABOOST) for an accurate and precise classification of epileptic signals. Validation of the proposed method is conducted using EEG data from the BEED (Bangalore EEG Epilepsy Dataset) and BONN (University of BONN, Germany) database to detect epileptic seizures. The experimental results show remarkably high levels of classification accuracy for various conditions: 99% accuracy for BEED data, 98% accuracy for BONN data for classifying seizures from healthy states, and 91% accuracy for classifying seizure onset from seizure events. Furthermore, the study applies the Gaussian Nae Bayes (GNB) classifier to differentiate various types of epileptic seizures, employing evaluation metrics such as the confusion matrix, ROC curve, and diverse performance measures. This method demonstrates significant potential in supporting experienced neurophysiologists decision in the clinical classification of epileptic seizure types. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. Creator An entity primarily responsible for making the resource Najmusseher; Banu P.K.N.; Azar A.T.; Kamal N.A. Source A related resource from which the described resource is derived Lecture Notes on Data Engineering and Communications Technologies, Vol-220, pp. 317-329. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-3-031-71619-5_27" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-71619-5_27</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85207939650&amp;doi=10.1007%2F978-3-031-71619-5_27&amp;partnerID=40&amp;md5=78c23f5bba59671d8459fbe910db047f" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85207939650&amp;doi=10.1007%2f978-3-031-71619-5_27&amp;partnerID=40&amp;md5=78c23f5bba59671d8459fbe910db047f</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23674512 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Najmusseher, Department of Computer Science, CHRIST (Deemed to Be University) Central Campus, Karnataka, Bangalore, 560029, India; Banu P.K.N., Department of Computer Science, CHRIST (Deemed to Be University) Central Campus, Karnataka, Bangalore, 560029, India; Azar A.T., College of Computer and Information Sciences, Prince Sultan University, Riyadh, 11586, Saudi Arabia, Faculty of Computers and Artificial Intelligence, Benha University, Benha, 13518, Egypt; Kamal N.A., Faculty of Engineering, Cairo University, Giza, Egypt