Complex Network Analysis of EEG Signals of Epilepsy Patients
Küçük Resim Yok
Tarih
2024
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Electroencephalography (EEG) signals have significant potential for understanding brain dynamics and cognitive processes. Analyzing EEG signals using traditional methods often faces difficulties in revealing complex relationships between different brain regions. In this study, complex connection structures in EEG data of epilepsy patients were revealed and interpreted with the complex network theory, whose application area has expanded in recent years. The average degree, diameter, density, modularity and clustering coefficients of EEG signals of different epileptic conditions converted into complex networks were calculated. Differences between EEG signals were interpreted by interpreting the calculated metrics. Topological metrics obtained from EEG signals show that complex network theory is applicable in classifying epilepsy patients. © 2024 IEEE.
Açıklama
Berdan Civata B.C.; et al.; Figes; Koluman; Loodos; Tarsus University
32nd IEEE Conference on Signal Processing and Communications Applications, SIU 2024 -- 15 May 2024 through 18 May 2024 -- Mersin -- 201235
32nd IEEE Conference on Signal Processing and Communications Applications, SIU 2024 -- 15 May 2024 through 18 May 2024 -- Mersin -- 201235
Anahtar Kelimeler
complex networks, data mining, time series
Kaynak
32nd IEEE Conference on Signal Processing and Communications Applications, SIU 2024 - Proceedings
WoS Q Değeri
Scopus Q Değeri
N/A
