Seizure detection using common spatial patterns and classification techniquesSeizure detection using common spatial patterns and classification techniques Πλήρης Δημοσίευση σε Συνέδριο Conference Full Paper 2020-04-222019enThis paper investigates the effectiveness of Common Spatial Patterns (CSP) analysis of EEG signals on the automatic detection of focal epileptic seizures. Focal seizures are characterized by unilaterally triggered abnormal brain activity. CSP analysis has been frequently used in literature for multichannel EEG signal separation between two states. In the present study, EEG recordings from 10 subjects aged 7.7±4.4 years, including 63 seizures, were analyzed with respect to seizure detection and discrimination between interictal and ictal periods. Machine learning techniques of feature selection and classification were used in the analysis, resulting in a best achieved classification accuracy of 91.1%.http://creativecommons.org/licenses/by/4.0/890-89319th International Conference on Bioinformatics and BioengineeringProceedings - 2019 IEEE 19th International Conference on Bioinformatics and Bioengineering Giannakakis Georgios Γιαννακακης Γεωργιος Tsekos Nikolaos Τσεκος Νικολαος Giannakaki Aikaterini-Antonia Γιαννακακη Αικατερινη-Αντωνια Michalopoulos Kostas Vorgia Pelagia Zervakis Michail Ζερβακης Μιχαηλ Institute of Electrical and Electronics Engineers Common spatial patterns CSP EEG Focal epilepsy Seizure detection