A computer-aided approach to detect the fetal behavioral states using multi-sensor Magnetocardiographic recordings

Ulusar, Umit Deniz; Eswaran, Hari; Preißl, Hubert; Wilson, James D.; McKelvey, Samantha S.; Lowery, Curtis L.; Govindan, Rathinaswamy B.

doi:10.1016/j.compbiomed.2015.11.017

Cited by 13 publications

(24 citation statements)

References 35 publications

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“…Nevertheless, the described method has been consistently used over the last years, was able to cluster fHRV results accordingly and has been adapted by research colleagues worldwide [ 4 , 14 , 18 – 22 , 37 , 38 ]. More recent efforts have been made to include fetal movements into analysis [ 23 , 39 ]. The resemblance of results between unclassified data and those, attributed to active fetal sleep in our present study, makes it unlikely that additional information on state appearance will cast doubt on the general principles elaborated here.…”

Section: Discussionmentioning

confidence: 99%

Developmental milestones of the autonomic nervous system revealed via longitudinal monitoring of fetal heart rate variability

et al. 2018

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BackgroundFetal heart rate variability (fHRV) of normal-to-normal (NN) beat intervals provides high-temporal resolution access to assess the functioning of the autonomic nervous system (ANS).AimTo determine critical periods of fetal autonomic maturation. The developmental pace is hypothesized to change with gestational age (GA).Study designProspective longitudinal observational study.Subjects60 healthy singleton fetuses were followed up by fetal magnetocardiographic heart rate monitoring 4–11 times (median 6) during the second half of gestation.Outcome measureFHRV parameters, accounting for differential aspects of the ANS, were studied applying linear mixed models over four predefined pregnancy segments of interest (SoI: <27; 27+0–31+0; 31+1–35+0; >35+1 weeks GA). Periods of fetal active sleep and quiescence were accounted for separately.ResultsSkewness of the NN interval distribution VLF/LF band power ratio and complexity describe a saturation function throughout the period of interest. A decreasing LF/HF ratio and an increase in pNN5 indicate a concurrent shift in sympathovagal balance. Fluctuation amplitude and parameters of short-term variability (RMSSD, HF band) mark a second acceleration towards term. In contrast, fetal quiescence is characterized by sequential, but low-margin transformations; ascending overall variability followed by an increase of complexity and superseded by fluctuation amplitude.ConclusionsAn increase in sympathetic activation, connected with by a higher ability of parasympathetic modulation and baseline stabilization, is reached during the transition from the late 2nd into the early 3rd trimester. Pattern characteristics indicating fetal well-being saturate at 35 weeks GA. Pronounced fetal breathing efforts near-term mirror in fHRV as respiratory sinus arrhythmia.

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Section: Discussionmentioning

confidence: 99%

Developmental milestones of the autonomic nervous system revealed via longitudinal monitoring of fetal heart rate variability

et al. 2018

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“…Electrodes with artifact >30 percent of the time were removed from analysis. Newborn’s state was classified into quiet and active based on HR acceleration 16,17 . We considered newborns who had at least one 5 minute EEG in both active and quiet state to be of high-quality.…”

Section: Methodsmentioning

confidence: 99%

The effect of labor and delivery mode on electrocortical and brainstem autonomic function during neonatal transition

Mulkey

Kota

Govindan

et al. 2019

Sci Rep

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Delivery of the newborn occurs either vaginally or via caesarean section. It is not known whether the mode of delivery and exposure to labor affects early autonomic nervous system (ANS) function, as measured by heart rate variability (HRV), or cortical electroencephalogram (EEG) activity. The objective of the study was to determine if autonomic function in newborns differs by mode of delivery. Simultaneous recording of EEG and electrocardiogram were collected in low-risk term newborns at <72 hours of age to measure HRV, the asymmetry index, and EEG power. Newborns were compared by delivery type: vaginal delivery (VD), cesarean section (CS) after labor (L-CS), or elective CS (E-CS). Quantile Regression controlled for gestational age, postnatal age, and percent active states. One hundred and eighteen newborns were studied at 25.2 (11.4) hours of age. Sixty-two (52.5%) were born by VD, 22 by L-CS (18.6%), and 34 by E-CS (28.8%). HRV metrics didn’t differ by delivery mode. Asymmetry index was higher in L-CS compared to VD and E-CS (P = 0.03). On EEG, L-CS newborns showed lower relative gamma power compared to VD and E-CS (P = 0.005). The study found that overall ANS tone is not altered by mode of delivery in low-risk term newborns.

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“…The fetal behavioural state underlying the datasets was automatically detected using an algorithm adapted from the work of Vairavan et al 14 and implemented in Matlab R2019b.…”

Section: Methodsmentioning

confidence: 99%

“…The early group includes datasets from fetuses between 27 and 32 (27 0/1–32 6/7) weeks of GA, the middle group fetuses between 33 and 36 (33 0/1–36 6/7) weeks of GA, and the late group includes fetuses between 37 and 39 (37 0/1–39 6/7) weeks GA. According to the work of Vairavan et al 14 , the percentage of accelerations in the HR, the standard deviation of the HR (σ(HR)) and the percentage of points above 160 bmp were computed. The thresholds for these values used in our algorithm are also from Vairavan and collaborators 14 .…”

Section: Methodsmentioning

confidence: 99%

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Evaluation of parameters for fetal behavioural state classification

Semeia

Sippel

Moser

et al. 2022

Sci Rep

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Fetal behavioural states (fBS) describe periods of fetal wakefulness and sleep and are commonly defined by features such as body and eye movements and heart rate. Automatic state detection through algorithms relies on different parameters and thresholds derived from both the heart rate variability (HRV) and the actogram, which are highly dependent on the specific datasets and are prone to artefacts. Furthermore, the development of the fetal states is dynamic over the gestational period and the evaluation usually only separated into early and late gestation (before and after 32 weeks). In the current work, fBS detection was consistent between the classification algorithm and visual inspection in 87 fetal magnetocardiographic data segments between 27 and 39 weeks of gestational age. To identify how automated fBS detection could be improved, we first identified commonly used parameters for fBS classification in both the HRV and the actogram, and investigated their distribution across the different fBS. Then, we calculated a receiver operating characteristics (ROC) curve to determine the performance of each parameter in the fBS classification. Finally, we investigated the development of parameters over gestation through linear regression. As a result, the parameters derived from the HRV have a higher classification accuracy compared to those derived from the body movement as defined by the actogram. However, the overlapping distributions of several parameters across states limit a clear separation of states based on these parameters. The changes over gestation of the HRV parameters reflect the maturation of the fetal autonomic nervous system. Given the higher classification accuracy of the HRV in comparison to the actogram, we suggest to focus further research on the HRV. Furthermore, we propose to develop probabilistic fBS classification approaches to improve classification in less prototypical datasets.

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A computer-aided approach to detect the fetal behavioral states using multi-sensor Magnetocardiographic recordings

Cited by 13 publications

References 35 publications

Developmental milestones of the autonomic nervous system revealed via longitudinal monitoring of fetal heart rate variability

Developmental milestones of the autonomic nervous system revealed via longitudinal monitoring of fetal heart rate variability

The effect of labor and delivery mode on electrocortical and brainstem autonomic function during neonatal transition

Evaluation of parameters for fetal behavioural state classification

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