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Abstract
Cardiotocography (CTG) is currently the most often used technique for detection of fetal distress. Unfortunately, CTG has a poor specificity. Recent studies suggest that, in addition to CTG, information on fetal distress can be obtained from analysis of fetal heart rate variability (HRV). However, uterine contractions can strongly influence fetal HRV. The aim of this study is therefore to investigate whether HRV analysis for detection of fetal distress can be improved by distinguishing contractions from rest periods. Our results from feature selection indicate that HRV features calculated separately during contractions or during rest periods are more informative on fetal distress than HRV features that are calculated over the entire fetal heart rate. Furthermore, classification performance improved from a geometric mean of 69.0% to 79.6% when including the contraction-dependent HRV features, in addition to HRV features calculated over the entire fetal heart rate.
Original language | English |
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Title of host publication | 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016, 16-18 August 2016, Orlando, Florida |
Place of Publication | Piscataway |
Publisher | Institute of Electrical and Electronics Engineers |
Pages | 2950-2953 |
Number of pages | 4 |
ISBN (Electronic) | 978-1-4577-0220-4 |
ISBN (Print) | 978-1-4577-0219-8 |
DOIs | |
Publication status | Published - 13 Oct 2016 |
Event | 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016 - Disney’s Contemporary Resort , Orlando, United States Duration: 16 Aug 2016 → 20 Aug 2016 Conference number: 38 http://embc.embs.org/2016/ |
Conference
Conference | 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016 |
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Abbreviated title | EMBC 2016 |
Country/Territory | United States |
City | Orlando |
Period | 16/08/16 → 20/08/16 |
Internet address |
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Dive into the research topics of 'Selective heart rate variability analysis to account for uterine activity during labor and improve classification of fetal distress'. Together they form a unique fingerprint.Projects
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Impacts
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Perinatal Medicine
M.B. (Beatrijs) van der Hout-van der Jagt (Content manager) & Eugenie Delvaux (Content manager)
Impact: Research Topic/Theme (at group level)