Development of multiscale complexity and multifractality of fetal heart rate variability

Gieraltowski, Jan; Hoyer, Dirk; Tetschke, Florian; Nowack, Samuel; Schneider, Uwe; Żebrowski, Jan J.

doi:10.1016/j.autneu.2013.01.009

Cited by 47 publications

(21 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Various linear and nonlinear analysis of fHRV have been applied for the classification of abnormal and compromised foetus [55,56]. These applications are encouraged by the findings that recommendations of standard for adult HRV analysis are not directly applicable to fHRV [22][23][24][25].…”

Section: Discussionmentioning

confidence: 98%

Analysis of fetal heart rate asymmetry before and after 35 weeks of gestation

Karmakar

Kimura

Palaniswami

et al. 2015

Biomedical Signal Processing and Control

View full text Add to dashboard Cite

a b s t r a c tIn this study, we have investigated the evidence of fetal heart rate asymmetry and how the fetal heart rate asymmetry changes before and after 35 weeks of gestation. Noninvasive fetal electrocardiogram (fECG) signals from 45 pregnant women at the gestational age from16 to 41 weeks with normal single pregnancies were analysed. A nonlinear parameter called heart rate asymmetry (HRA) index that measures time asymmetry of RR interval time-series signal was used to understand the changes of HRA in early and late fetus groups. Results indicate that fetal HRA measured by Porta's Index (PI) consistently increases after 35 weeks gestation compared to foetus before 32 weeks of gestation. It might be due to significant changes of sympatho-vagal balance towards delivery with more sympathetic surge. On the other hand, Guzik's Index (GI) showed a mixed effect i.e., increases at lower lags and decreases at higher lags. Finally, fHRA could potentially help identify normal and the pathological autonomic nervous system development.

show abstract

Section: Discussionmentioning

confidence: 98%

Analysis of fetal heart rate asymmetry before and after 35 weeks of gestation

Karmakar

Kimura

Palaniswami

et al. 2015

Biomedical Signal Processing and Control

View full text Add to dashboard Cite

show abstract

“…Linear and nonlinear analysis of foetal heart rate variability have been applied for some time for the classification of abnormal and compromised foetuses [13,14]. These methods differ in terms of their appropriateness for analysis of the foetal HRV (fHRV) including the measurement of foetal heart rate techniques.…”

Section: Discussionmentioning

confidence: 99%

Tone Entropy Analysis of Foetal Heart Rate Variability

Khandoker

Karmakar

Kimura

et al. 2015

Entropy

View full text Add to dashboard Cite

Development of the foetal autonomic nervous system can be indirectly understood by looking at the changes in beat to beat variability in foetal heart rates. This study presents Tone-Entropy (T-E) analysis of foetal heart rate variability (HRV) at multiple lags (1-8) to understand the influence of gestational ages (early and late) on the development of the foetal autonomic nervous system (ANS). The analysis was based on foetal electrocardiograms (FECGs) of 46 healthy foetuses of 20-32 weeks (early group) and 22 foetuses of 35-41 weeks (late group). Tone represents sympatho-vagal balance and entropy the total autonomic activities. Results show that tone increases and entropy decreases at all lags for the late foetus group. On the other hand, tone decreases and entropy increases at lags 1-4 in the early foetus group. Increasing tone in late foetuses might represent significant maturation of sympathetic nervous systems because foetuses approaching to delivery period need increased sympathetic activity. T-E could be quantitative clinical index to determine the early foetuses from late ones on the basis of maturation of autonomic nervous system.

show abstract

“…In order to quantify time-correlations in recorded time series, we have used the DFA method [36,37], frequently applied in analysis of physiological data [25,[38][39][40][41]. The original time series X(t), t = 1, ..., N have been integrated Z(k) = k t=1 [X(t) − X], where X = N t=1 X(t)/N is the data mean and k is an integer number k ∈ {1, ..., N }.…”

Section: Detrended Fluctuation Analysis and Hurst Exponentmentioning

confidence: 99%

Seeking a fingerprint: analysis of point processes in actigraphy recording

Gudowska–Nowak¹,

Ochab²,

Oleś³

et al. 2016

J. Stat. Mech.

View full text Add to dashboard Cite

Motor activity of humans displays complex temporal fluctuations which can be characterized by scale-invariant statistics, thus documenting that structure and fluctuations of such kinetics remain similar over a broad range of time scales. Former studies on humans regularly deprived of sleep or suffering from sleep disorders predicted change in the invariant scale parameters with respect to those representative for healthy subjects. In this study we investigate the signal patterns from actigraphy recordings by means of characteristic measures of fractional point processes. We analyse spontaneous locomotor activity of healthy individuals recorded during a week of regular sleep and a week of chronic partial sleep deprivation. Behavioural symptoms of lack of sleep can be evaluated by analysing statistics of duration times during active and resting states, and alteration of behavioural organization can be assessed by analysis of power laws detected in the event count distribution, distribution of waiting times between consecutive movements and detrended fluctuation analysis of recorded time series. We claim that among different measures characterizing complexity of the actigraphy recordings and their variations implied by chronic sleep distress, the exponents characterizing slopes of survival functions in resting states are the most effective biomarkers distinguishing between healthy and sleep-deprived groups.

show abstract

Development of multiscale complexity and multifractality of fetal heart rate variability

Cited by 47 publications

References 37 publications

Analysis of fetal heart rate asymmetry before and after 35 weeks of gestation

Analysis of fetal heart rate asymmetry before and after 35 weeks of gestation

Tone Entropy Analysis of Foetal Heart Rate Variability

Seeking a fingerprint: analysis of point processes in actigraphy recording

Contact Info

Product

Resources

About