Using Nonlinear Features for Fetal Heart Rate Classification

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F12%3A00193060" target="_blank" >RIV/68407700:21230/12:00193060 - isvavai.cz</a>
Alternative codes found
RIV/65269705:_____/12:#0001674 RIV/00064165:_____/12:13565
Result on the web
<a href="http://www.sciencedirect.com/science/article/pii/S1746809411000619" target="_blank" >http://www.sciencedirect.com/science/article/pii/S1746809411000619</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.bspc.2011.06.008" target="_blank" >10.1016/j.bspc.2011.06.008</a>

Result language
angličtina
Original language name
Using Nonlinear Features for Fetal Heart Rate Classification
Original language description
Fetal heart rate (FHR) is used to evaluate fetal well-being and enables clinicians to detect ongoing hypoxia during delivery. Routine clinical evaluation of intrapartum FHR is based on macroscopic morphological features visible to the naked eye. In thispaper we evaluated conventional features and compared them to the nonlinear ones in the task of intrapartum FHR classification. The experiments were performed using a database of 217 FHR records with objective annotations, i.e. pH measurement. We have proven that the addition of nonlinear features improves accuracy of classification. The best classification results were achieved using a combination of conventional and nonlinear features with sensitivity of 73.4%, specificity of 76.3%, and F-measure of 71.9%. The best selected nonlinear features were: Lempel Ziv complexity, Sample entropy, and fractal dimension estimated by Higuchi method. Since the results of automatic signal evaluation are easily reproducible, the process of FHR evalua
Czech name
—
Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
JC - Computer hardware and software
OECD FORD branch
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Project
<a href="/en/project/NT11124" target="_blank" >NT11124: Impact of Cardiotocography evaluation by means of artificial inteligence on perinatal care</a><br>
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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