A novel software for comprehensive analysis of cardiotocography signals "CTG-OAS"

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dc.authorscopusid36543652400
dc.authorscopusid54882441600
dc.contributor.authorCömert Z.
dc.contributor.authorKocamaz A.F.
dc.date.accessioned2024-08-04T20:03:56Z
dc.date.available2024-08-04T20:03:56Z
dc.date.issued2017
dc.departmentİnönü Üniversitesien_US
dc.description2017 International Artificial Intelligence and Data Processing Symposium, IDAP 2017 -- 16 September 2017 through 17 September 2017 -- 115012en_US
dc.description.abstractThe research interest in fetal heart rate (FHR) monitoring dates back to the 1960s, and the breakthrough on fetal surveillance has been seen during the 1990s with computerized systems. Notwithstanding the general use of cardiotocography (CTG) in fetal monitoring, the assessment of fetal well-being exhibits a significant inter- and even intraobserver variability. Computerized CTG analysis has seen as the most promising way to tackle of the main shortcomings of visual CTG assessment. In this study, a novel software developed for research purposes is introduced. The software named as CTG Open Access Software (CTG-OAS) characterizes FHR signals by using comprehensive features obtained from different fields such as morphological, linear, nonlinear, time-frequency, discrete wavelet transform, and image-based time-frequency domains. The software also covers the main procedures which are necessary for the context of machine learning. More specifically, CTG-OAS presents several tools for performing the preprocessing, feature extraction, feature selection, and classification processes. The proposed software was practiced on CTU-UHB database with 552 raw CTG samples. In addition, a case study with Support Vector Machine classifier was performed in the study via CTG-OAS. According to experimental results, statistical parameters were obtained as accuracy equal to 87.97%, sensitivity equal to 89.04%, specificity equal to 81.36% and, quality index equal to 85.11%. © 2017 IEEE.en_US
dc.identifier.doi10.1109/IDAP.2017.8090210
dc.identifier.isbn9781538618806
dc.identifier.scopus2-s2.0-85039901726en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1109/IDAP.2017.8090210
dc.identifier.urihttps://hdl.handle.net/11616/92224
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofIDAP 2017 - International Artificial Intelligence and Data Processing Symposiumen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBiomedical signal processingen_US
dc.subjectCardiotocographyen_US
dc.subjectClassificationen_US
dc.subjectFetal heart rateen_US
dc.subjectMachine learningen_US
dc.subjectSoftwareen_US
dc.titleA novel software for comprehensive analysis of cardiotocography signals "CTG-OAS"en_US
dc.typeConference Objecten_US

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