A distance-based dynamical transition analysis of time series signals and application to biological systems

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dc.authoridAlagoz, Serkan/0000-0003-2642-8462
dc.authoridAlagoz, Baris Baykant/0000-0001-5238-6433
dc.authorwosidAlagoz, Serkan/ABI-2130-2020
dc.authorwosidAlagoz, Baris Baykant/ABG-8526-2020
dc.contributor.authorAlagoz, Serkan
dc.contributor.authorAlagoz, Baris Baykant
dc.date.accessioned2024-08-04T20:36:01Z
dc.date.available2024-08-04T20:36:01Z
dc.date.issued2012
dc.departmentİnönü Üniversitesien_US
dc.description.abstractThis study demonstrates an application of distance-based numerical measures to the phase space of time series signals, in order to obtain a temporal analysis of complex dynamical systems. This method is capable of detecting alterations appearing in the characters of the deterministic dynamical systems and provides a simple tool for the real-time analysis of time series data obtained from a complex dynamical system even with black box functionality. The study presents a possible application of the method in the dynamical transition analysis of real EEG records from epilepsy patients.en_US
dc.description.sponsorshipNeurology Departmenten_US
dc.description.sponsorshipWe thank Prof. Dr. Cemal Ozcan and staff of Neurology Department for their support to our biomedical signal processing studies with EEG data. We also thank Dr. M. Emin Tagluk for fruitful conversations.en_US
dc.identifier.doi10.1007/s10867-011-9248-2
dc.identifier.endpage303en_US
dc.identifier.issn0092-0606
dc.identifier.issue2en_US
dc.identifier.pmid23449743en_US
dc.identifier.scopus2-s2.0-84863858688en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage293en_US
dc.identifier.urihttps://doi.org/10.1007/s10867-011-9248-2
dc.identifier.urihttps://hdl.handle.net/11616/95722
dc.identifier.volume38en_US
dc.identifier.wosWOS:000302868400008en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofJournal of Biological Physicsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectDynamical system analysisen_US
dc.subjectChaosen_US
dc.subjectEpilepsy seizure prediction from EEG signalen_US
dc.titleA distance-based dynamical transition analysis of time series signals and application to biological systemsen_US
dc.typeArticleen_US

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