Foetal heart rate variability frequency characteristics with respect to uterine contractions

Cesarelli, Mario; Romano, Maria; Ruffo, M.; Bifulco, Paolo; Pasquariello, G.

doi:10.4236/jbise.2010.310132

Cited by 17 publications

(16 citation statements)

References 29 publications

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“…As a result of this uncontrolled environment, HRV features are often calculated over highly non-stationary FHR signals. This is also indicated by Romano et al (2006) and Cesarelli et al (2010), who showed that for healthy fetuses spectral power is significantly higher during contractions as compared to rest periods (i.e. the periods in between contractions).…”

Section: Introductionsupporting

confidence: 55%

Using uterine activity to improve fetal heart rate variability analysis for detection of asphyxia during labor

et al. 2016

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During labor, uterine contractions can cause temporary oxygen deficiency for the fetus. In case of severe and prolonged oxygen deficiency this can lead to asphyxia. The currently used technique for detection of asphyxia, cardiotocography (CTG), suffers from a low specificity. Recent studies suggest that analysis of fetal heart rate variability (HRV) in addition to CTG can provide information on fetal distress. However, interpretation of fetal HRV during labor is difficult due to the influence of uterine contractions on fetal HRV. The aim of this study is therefore to investigate whether HRV features differ during contraction and rest periods, and whether these differences can improve the detection of asphyxia. To this end, a case-control study was performed, using 14 cases with asphyxia that were matched with 14 healthy fetuses. We did not find significant differences for individual HRV features when calculated over the fetal heart rate without separating contractions and rest periods (p > 0.30 for all HRV features). Separating contractions from rest periods did result in a significant difference. In particular the ratio between HRV features calculated during and outside contractions can improve discrimination between fetuses with and without asphyxia (p < 0.04 for three out of four ratio HRV features that were studied in this paper).

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Section: Introductionsupporting

confidence: 55%

Using uterine activity to improve fetal heart rate variability analysis for detection of asphyxia during labor

et al. 2016

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“…The best classification performance was achieved by the features sets CS 4 , CS 11 , CS 12 , and DR 5 , where two of them correspond to modal-spectral, whereas the other two sets correspond to conventional features. As presented in Tables 2 and 4, the select sets were extracted from the indicators IMF 4 -E c , FHR signal, PBL, and IMF 6 -E, respectively.…”

Section: Features Evaluation and Discussionmentioning

confidence: 99%

“…These compensatory mechanisms are controlled by the autonomic nervous system (ANS), which modulates the fetal cardiac activity after a perceived oxygen insufficiency [10,11]. Indeed, the fetal compensation response, represented by variations in the beat-to-beat FHR, can involve important time-variant dynamics related to the fetal condition [12,13]. Given that concept, an appropriate FHR signal analysis should consider the nonlinear and non-stationary characteristics of the compensatory mechanism.…”

Section: Introductionmentioning

confidence: 99%

Independent Analysis of Decelerations and Resting Periods through CEEMDAN and Spectral-Based Feature Extraction Improves Cardiotocographic Assessment

2019

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Fetal monitoring is commonly based on the joint recording of the fetal heart rate (FHR) and uterine contraction signals obtained with a cardiotocograph (CTG). Unfortunately, CTG analysis is difficult, and the interpretation problems are mainly associated with the analysis of FHR decelerations. From that perspective, several approaches have been proposed to improve its analysis; however, the results obtained are not satisfactory enough for their implementation in clinical practice. Current clinical research indicates that a correct CTG assessment requires a good understanding of the fetal compensatory mechanisms. In previous works, we have shown that the complete ensemble empirical mode decomposition with adaptive noise, in combination with time-varying autoregressive modeling, may be useful for the analysis of those characteristics. In this work, based on this methodology, we propose to analyze the FHR deceleration episodes separately. The main hypothesis is that the proposed feature extraction strategy applied separately to the complete signal, deceleration episodes, and resting periods (between contractions), improves the CTG classification performance compared with the analysis of only the complete signal. Results reveal that by considering the complete signal, the classification performance achieved 81.7% quality. Then, including information extracted from resting periods, it improved to 83.2%.

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“…Because of the non-stationariety of the FHRV signal and according to the literature and methodologies previously used by the authors [21,22,23], the power spectral density (PSD) was estimated by means of the Short Time Fourier Transformation using a sliding Hamming window of 32 s [24]. Then, we computed the power in the main frequency bands of FHRV.…”

Section: Frequency Domain Analysismentioning

confidence: 99%

Symbolic dynamic and frequency analysis in foetal monitoring

Romano

D’Addio

Clemente³

et al. 2014

2014 IEEE International Symposium on Medical Measurements and Applications (MeMeA)

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Foetal heart rate variability is widely considered an important parameter to assess foetal reactivity and wellbeing. Traditional approaches to analyze foetal heart rate and its variability, such as Time and Frequency Domain Analyses, have shown some limitations, due to their inability to highlight nonlinear dynamics potentially relevant. Hence, in the last decades, nonlinear analysis methods have gained a growing interest and the integration of parameters derived from these techniques and traditional ones could be a way to improve the assessment of foetal development and/or distress. In this work, we proposed a comparison between new index obtained with a nonlinear analysis (Symbolic Dynamic Analysis) and more traditional parameters computed by the power spectral density of the foetal heart variability signals (Frequency Domain Analysis). A dataset of 579 cardiotocographic signals from healthy foetuses, recorded from the 24th to the 42th gestation week, was examined using both above-mentioned methods. The obtained results demonstrate that Symbolic Dynamics, as much as Frequency Domain Analysis, could be a useful tool in foetal development assessing. �� 2014 IEEE

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Foetal heart rate variability frequency characteristics with respect to uterine contractions

Cited by 17 publications

References 29 publications

Using uterine activity to improve fetal heart rate variability analysis for detection of asphyxia during labor

Using uterine activity to improve fetal heart rate variability analysis for detection of asphyxia during labor

Independent Analysis of Decelerations and Resting Periods through CEEMDAN and Spectral-Based Feature Extraction Improves Cardiotocographic Assessment

Symbolic dynamic and frequency analysis in foetal monitoring

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