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  4. Наукові публікації працівників кафедри біотехнічних систем
Ezzel az azonosítóval hivatkozhat erre a dokumentumra forrásmegjelölésben vagy hiperhivatkozás esetén: http://elartu.tntu.edu.ua/handle/lib/50397
Összes dokumentumadat
DC mezőÉrtékNyelv
dc.contributor.authorKhvostivskyi, Mykola-
dc.contributor.authorTalalai, Ihor-
dc.date.accessioned2025-12-12T18:24:51Z-
dc.date.available2025-12-12T18:24:51Z-
dc.date.issued2025-11-10-
dc.identifier.citationKhvostivskyi M., Talalai I. Adaptive detection of epileptic activity in EEG signals based on morphological analysis and the neyman-pearson criterion. Collection of Scientific Papers with the Proceedings of the 4th International Scientific and Practical Conference «Achievements of Science and Applied Research» (November 10-12, 2025. Dublin, Ireland). European Open Science Space, 2025. P.367-371. DOI: 10.70286/EOSS-10.11.2025.uk_UA
dc.identifier.isbn979-8-89704-961-5-
dc.identifier.urihttp://elartu.tntu.edu.ua/handle/lib/50397-
dc.format.extent367-371-
dc.language.isoenuk_UA
dc.publisherEuropean Open Science Spaceuk_UA
dc.titleAdaptive detection of epileptic activity in EEG signals based on morphological analysis and the Neyman-Pearson criterionuk_UA
dc.typeConference Abstractuk_UA
dc.rights.holder© Khvostivskyi M., Talalai I.uk_UA
dc.coverage.placenameDublin, Irelanduk_UA
dc.relation.referencesen1. Cerf R., el-Ouasdad E.H. Spectral analysis for early detection of epileptic seizures. Medical & Biological Engineering & Computing. 2008. Vol. 46, No. 4. P. 379-386.uk_UA
dc.relation.referencesen2. Tsipouras M.G. Spectral information of EEG signals with respect to epilepsy classification. EURASIP J. Adv. Signal Process. 2019, 10 (2019). https://doi.org/10.1186/s13634-019-0606-8.uk_UA
dc.relation.referencesen3. Tian C., Zhang F. EEG-based epilepsy detection with graph correlation analysis. Frontiers in Medicine. 2025. Vol. 12, Article 1549491. DOI: 10.3389/fmed.2025.1549491.uk_UA
dc.relation.referencesen4. Diego Rielo, Selim R. Benbadis MD. Correlation studies in epileptic EEG patterns. Seizure. 2004. Vol. 13, No. 7. P. 475-483.uk_UA
dc.relation.referencesen5. Roy Sucholeiki, Alarcon G., Binnie C.D., C. Elwes R.D., Polkey C.E., Starykh E.V. Spectral-correlation methods for epilepsy EEG analysis. Electroencephalography and Clinical Neurophysiology. 2002. Vol. 103, No. 6. P. 536-548.uk_UA
dc.relation.referencesen6. A.T. Tzallas, M.G. Tsipouras, D.I. Fotiadis, Starykh E.V. Time-frequency analysis of EEG in epileptic patients. IEEE Transactions on Information Technology in Biomedicine. 2007. Vol. 11, No. 3. P. 327-335.uk_UA
dc.relation.referencesen7. Ocak H., Bhattacharyya A., Pachori R.B., Upadhyay A., Acharya U.R. Wavelet decomposition of EEG and entropy computation for seizure classification. Computers in Biology and Medicine. 2011. Vol. 41, No. 12. P. 1090-1097.uk_UA
dc.relation.referencesen8. Khvostivskyy M., Khvostivska L, Boyko R. Software, mathematical and algorithmic tools for the computer electroencephalography system of humans epilepsy manifestations detecting. Visnyk NTUU KPI Seriia - Radiotekhnika Radioaparatobuduvannia. 84 (Mar. 2021), P. 66-77. DOI: https://doi.org/10.20535/RADAP.2021.84.66-77.uk_UA
dc.relation.referencesen9. Khvostivskyi M., Boiko R. Method and software for processing daily EEG signals for detection of epileptic seizures in humans. Scientific Journal of TNTU (Tern.), 2024. Vol 113, no 1, P. 119–130. URL: https://visnyk.tntu.edu.ua/?art=772.uk_UA
dc.relation.referencesen10. Boyko R., Khvostivskyi M., Fuch O. Mathematical Model of the 24-hour EEG Signal of People with Manifestations of Epilepsy for Computer EEG Systems. Proceedings of the XXVII International Scientific and Practical Conference. Edmonton, Canada. 2023. Pp. 179-184.uk_UA
dc.relation.referencesen11. Khvostivskyy M.O., Fuch O.V., Khvostivska L.V. Mathematical Model of EEG-Signals at Psycho-Emotional Influence. Science and Industry. Abstracts of the 34th International scientific and practical conference. Littera Verlag, Berlin. 2022. Pp. 167-171. ISBN 978-3-9110125-1-5.uk_UA
dc.identifier.citationenAPAKhvostivskyi, M., & Talalai, I. (2025). Adaptive detection of epileptic activity in EEG signals based on morphological analysis and the Neyman–Pearson criterion. Achievements of Science and Applied Research: Proceedings of the 4th International Scientific and Practical Conference (Dublin, Ireland, November 10–12, 2025) (pp. 367–371). European Open Science Space. DOI: 10.70286/EOSS-10.11.2025.uk_UA
Ebben a gyűjteményben:Наукові публікації працівників кафедри біотехнічних систем

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