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Intrapartum fetal heart rate classification from trajectory in Sparse SVM feature space

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F15%3A00239724" target="_blank" >RIV/68407700:21730/15:00239724 - isvavai.cz</a>

  • Result on the web

    <a href="http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7318861&newsearch=true&queryText=%20Intrapartum%20fetal%20heart%20rate%20classification%20from%20trajectory%20in%20Sparse%20SVM%20feature%20spac" target="_blank" >http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7318861&newsearch=true&queryText=%20Intrapartum%20fetal%20heart%20rate%20classification%20from%20trajectory%20in%20Sparse%20SVM%20feature%20spac</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/EMBC.2015.7318861" target="_blank" >10.1109/EMBC.2015.7318861</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Intrapartum fetal heart rate classification from trajectory in Sparse SVM feature space

  • Original language description

    Intrapartum fetal heart rate (FHR) constitutes a prominent source of information for the assessment of fetal reactions to stress events during delivery. Yet, early detection of fetal acidosis remains a challenging signal processing task. The originalityof the present contribution are three-fold: multiscale representations and wavelet leader based multifractal analysis are used to quantify FHR variability ; Supervised classification is achieved by means of Sparse-SVM that aim jointly to achieve optimaldetection performance and to select relevant features in a multivariate setting ; Trajectories in the feature space accounting for the evolution along time of features while labor progresses are involved in the construction of indices quantifying fetal health. The classification performance permitted by this combination of tools are quantified on a intrapartum FHR large database (~ 1250 subjects) collected at a French academic public hospital.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    JC - Computer hardware and software

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/NT11124" target="_blank" >NT11124: Impact of Cardiotocography evaluation by means of artificial inteligence on perinatal care</a><br>

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2015

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    IEEE EMBC 2015 Proceedings (Milano)

  • ISBN

    9781424492718

  • ISSN

    1557-170X

  • e-ISSN

  • Number of pages

    4

  • Pages from-to

    2335-2338

  • Publisher name

    IEEE

  • Place of publication

    Milano

  • Event location

    Milano

  • Event date

    Aug 25, 2015

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article