Open-access software for analysis of fetal heart rate signals

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dc.authoridCömert, Zafer/0000-0001-5256-7648
dc.authoridKocamaz, Adnan Fatih/0000-0002-7729-8322
dc.authorwosidCömert, Zafer/V-1446-2019
dc.authorwosidKocamaz, Adnan Fatih/C-2820-2014
dc.contributor.authorComert, Zafer
dc.contributor.authorKocamaz, Adnan Fatih
dc.date.accessioned2024-08-04T20:44:35Z
dc.date.available2024-08-04T20:44:35Z
dc.date.issued2018
dc.departmentİnönü Üniversitesien_US
dc.description.abstractCardiotocography (CTG) comprises fetal heart rate (FHR) and uterine contraction (UC) signals that are simultaneously recorded. In clinical practice, a visual examination is subjectively performed by observers depending on the guidelines to evaluate CTG traces. Owing to this visual assessment, the variability in the interpretation of CTG between inter-and even intra-observers is considerably high. In addition, traditional clinical practice involves different human factors that distort the quantitative quality of the evaluation. Automated CTG analysis is the most promising way to tackle the main shortcomings of CTG by providing reproducibility of the evaluation as well as the quantitative results. In this study, open access software (CTG-OAS) developed with MATLAB is introduced for the analysis of FHR signals. The software contains important processes of the automated CTG analysis, from accessing the database to conducting model evaluations. In addition to traditionally used morphological, linear, nonlinear, and time-frequency features, the developed software introduces an innovative approach called image-based time-frequency features to characterize FHR signals. All functions of the software are well documented, and it is distributed freely for research purposes. In addition, an experimental study on the publicly accessible CTU-UHB database was performed using CTG-OAS to test the reliability of the software. The experimental study obtained results that included an accuracy of 77.81%, sensitivity of 76.83%, specificity of 78.27%, and geometric mean of 77.29%. These fairly promising results indicate that the software can be a valuable tool for the analysis of CTG signals. In addition, the results obtained using CTG-OAS can be easily compared to different algorithms. Moreover, different experimental setups can be designed using the tools provided by the software. Thus, the software can contribute to the development of new algorithms. (C) 2018 Elsevier Ltd. All rights reserved.en_US
dc.identifier.doi10.1016/j.bspc.2018.05.016
dc.identifier.endpage108en_US
dc.identifier.issn1746-8094
dc.identifier.issn1746-8108
dc.identifier.scopus2-s2.0-85048514713en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage98en_US
dc.identifier.urihttps://doi.org/10.1016/j.bspc.2018.05.016
dc.identifier.urihttps://hdl.handle.net/11616/98338
dc.identifier.volume45en_US
dc.identifier.wosWOS:000440774700010en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevier Sci Ltden_US
dc.relation.ispartofBiomedical Signal Processing and Controlen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBiomedical signal processingen_US
dc.subjectDecision support systemen_US
dc.subjectCardiotocographyen_US
dc.subjectSoftwareen_US
dc.subjectImage-based time-frequency featuresen_US
dc.titleOpen-access software for analysis of fetal heart rate signalsen_US
dc.typeArticleen_US

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