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dc.contributor.authorAghazadeh, R
dc.contributor.authorShahabi, P
dc.contributor.authorFrounchi, J
dc.contributor.authorSadighi, M
dc.date.accessioned2018-08-26T07:42:43Z
dc.date.available2018-08-26T07:42:43Z
dc.date.issued2015
dc.identifier.urihttp://dspace.tbzmed.ac.ir:8080/xmlui/handle/123456789/47867
dc.description.abstractThis paper presents a real-time, completely automated and patient independent algorithm for detection of absence seizures in WAG/Rij rats as a valid animal model of human absence epilepsy. Single-channel EEG recordings containing totally 488 seizures from 8 WAG/Rij rats were analyzed using the real-time SWD detection algorithm. The proposed algorithms based on the variation of wavelet power to the background power in two specific frequency bands whose spectral power are highly correlated with SWDs. The wavelet powers of two specific frequency bands are calculated with a pattern-adapted mother wavelet and compared with an adaptive ratio of background power of each frequency band. The results indicate used algorithm is able to detect the whole 488 seizures within less than 1 s with sensitivity of 100%. The average precision for 1200, 1400 and 1600 point of window size was 95.2%, 98.3% and 99.17%, respectively. The present algorithm, with its high sensitivity and specificity, could be used for further studies of absence seizures in humans and rats and could be implemented as real-time system for closed loop deep brain stimulation systems.
dc.language.isoEnglish
dc.relation.ispartofGENERAL PHYSIOLOGY AND BIOPHYSICS
dc.subjectAbsence epilepsy
dc.subjectEEG
dc.subjectWAG/Rij rats
dc.subjectWavelet analyses
dc.subjectPattern-adapted wavelet
dc.titleAn autonomous real-time single-channel detection of absence seizures in WAG/Rij rats
dc.typeArticle
dc.citation.volume34
dc.citation.issue3
dc.citation.spage285
dc.citation.epage291
dc.citation.indexWeb of science
dc.identifier.DOIhttps://doi.org/10.4149/gpb_2015010


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