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https://hdl.handle.net/20.500.13091/1558
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DC Field | Value | Language |
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dc.contributor.author | Yıldırım, Sema | - |
dc.contributor.author | Koçer, Hasan Erdinç | - |
dc.contributor.author | Ekmekçi, Ahmet Hakan | - |
dc.date.accessioned | 2021-12-13T10:41:32Z | - |
dc.date.available | 2021-12-13T10:41:32Z | - |
dc.date.issued | 2021 | - |
dc.identifier.issn | 0765-0019 | - |
dc.identifier.issn | 1958-5608 | - |
dc.identifier.uri | https://doi.org/10.18280/ts.380323 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.13091/1558 | - |
dc.description.abstract | Persistent, unchanging, and non-reactive focal or generalized abnormal Slow Wave (SW) activities in an awake adult patient are examined pathologically. Although these waves in Electroencephalogram (EEG) are much less prominent than transient activities in some areas, it is not possible to understand them easily by looking at the EEG. For this reason, reliable computer programs that can sort out Slow Waves (SWs) correctly are needed. In this study, a new method based on MinPeakProminence that can detect abnormal SW activities was developed. To test the performance of the study, the data collected from Selcuk University Hospital (22 subjects - epilepsy and various neurological diseases) and Bonn Hospital (only normal A dataset) were used. Various statistical performance measurement methods were used to search the results. The results of this analysis revealed that the classification success, sensitivity and specificity values obtained with the SUH dataset were 96.5%, 93.3% and 96.1%, respectively. In the results of the experiments made with the Bonn dataset, 100% classification success was achieved. Besides, according to the analyses, it was found that SWs are frequently seen in the posterior regions of the brain, especially in the parietal and occipital regions in the SUH dataset. | en_US |
dc.language.iso | en | en_US |
dc.publisher | INT INFORMATION & ENGINEERING TECHNOLOGY ASSOC | en_US |
dc.relation.ispartof | TRAITEMENT DU SIGNAL | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | Electroencephalogram | en_US |
dc.subject | Slow Wave | en_US |
dc.subject | Peak | en_US |
dc.subject | Minpeakprominence | en_US |
dc.subject | Epilepsy | en_US |
dc.subject | Neurologic Disorder | en_US |
dc.subject | Complex Partial Seizures | en_US |
dc.subject | Epileptic Seizures | en_US |
dc.subject | International-Bureau | en_US |
dc.subject | Classification | en_US |
dc.subject | Ilae | en_US |
dc.subject | League | en_US |
dc.subject | Spike | en_US |
dc.title | Quantitative Analysis of EEG Slow Wave Activity Based on MinPeakProminence Method | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.18280/ts.380323 | - |
dc.identifier.scopus | 2-s2.0-85111776693 | en_US |
dc.department | Fakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik-Elektronik Mühendisliği Bölümü | en_US |
dc.identifier.volume | 38 | en_US |
dc.identifier.issue | 3 | en_US |
dc.identifier.startpage | 757 | en_US |
dc.identifier.endpage | 773 | en_US |
dc.identifier.wos | WOS:000681761900023 | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.authorscopusid | 57216826829 | - |
dc.authorscopusid | 57210655277 | - |
dc.authorscopusid | 57212059303 | - |
dc.identifier.scopusquality | Q3 | - |
item.fulltext | With Fulltext | - |
item.openairetype | Article | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.grantfulltext | open | - |
item.cerifentitytype | Publications | - |
item.languageiso639-1 | en | - |
Appears in Collections: | Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections |
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File | Size | Format | |
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38.03_23.pdf | 2.51 MB | Adobe PDF | View/Open |
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