Prognostic decision support using symbolic dynamics in CTG monitoring

Mario Cesarelli, Maria Romano, Paolo Bifulco, Giovanni Improta, Giovanni D'Addio

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Foetal heart rate variability is one of the most important parameters to monitor foetal wellbeing. Linear parameters, widely employed to study foetal heart variability, have shown some limitations in highlight dynamics potentially relevant. During the last decades, therefore, nonlinear analysis methods have gained a growing interest to analyze the chaotic nature of cardiac activity. Parameters derived by techniques investigating nonlinear can be included in computerised systems of cardiotocographic monitoring. In this work, we described an application of symbolic dynamics to analyze foetal heart rate variability in healthy foetuses and a concise index, introduced for its classification in antepartum CTG monitoring. The introduced index demonstrated to be capable to highlight differences in heart rate variability and resulted correlated with the Apgar score at birth, in particular, higher variability indexes values are associated to early greater vitality at birth. These preliminary results confirm that SD can be a helpful tool in CTG monitoring, supporting medical decisions in order to assure the maximum well-being of newborns.

Original languageEnglish
Title of host publicationStudies in Health Technology and Informatics
PublisherIOS Press
Number of pages5
ISBN (Print)9781614992394
Publication statusPublished - 2013
Event13th EFMI Special Topic Conference: Data and Knowledge for Medical Decision Support, EFMI STC 2013 - Prague, Czech Republic
Duration: Apr 17 2013Apr 19 2013


Other13th EFMI Special Topic Conference: Data and Knowledge for Medical Decision Support, EFMI STC 2013
Country/TerritoryCzech Republic


  • Computerised cardiotocography
  • Foetal health monitoring
  • Foetal health prognostic decision support
  • Symbolic dynamics

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management


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