ArticlePloS one2024
Wearable-derived maternal heart rate variability as a novel digital biomarker of preterm birth.
Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- The menstrual cycle through the lens of a wearable device: insights into physiology, sleep, and cycle variability.NPJ digital medicine · 2026Article
- Benefit of the N-of-1 Approach Versus Aggregate Analysis in Tracking Individual Trajectories During Pregnancy: Comparison of Longitudinal Wearable Observational Studies.JMIR formative research · 2026Article
- Decoding menstrual health across the lifespan: a scoping review of digital health tools in research.medRxiv : the preprint server for health sciences · 2026Article
- From virtual pregnancy to digital twin obstetrics: multimodal data integration for personalized prediction of pregnancy complications.Frontiers in medicine · 2026Review
- Decoding menstrual health across the lifespan: a scoping review of digital health tools in research.npj women's health · 2026Article
- Heart Rate Variability Patterns Reflect Yoga Intervention in Chronically Stressed Pregnant Women: A Quasi-Randomized Controlled Trial.Bioengineering (Basel, Switzerland) · 2025Article
- Information Dynamics of the Mother-Fetus System Using Kolmogorov-Sinai Entropy Derived from Heart Sounds: A Longitudinal Study from Early Pregnancy to Postpartum.Entropy (Basel, Switzerland) · 2025Article
- A Scoping Review of Studies Reporting Heart Rate Variability Measurement Among Pregnant and Postpartum People Using Wearable Technology.Biological research for nursing · 2025Article
- Association of maternal nocturnal heart rate and adverse pregnancy outcomes.Pregnancy (Hoboken, N.J.) · 2025Article
- Investigating the role of maternal heart rate variability in the onset of labor.Frontiers in medicine · 2025Article
- Deep learning model using continuous skin temperature data predicts labor onset.BMC pregnancy and childbirth · 2024Article
- Preterm birth risk stratification through longitudinal heart rate and HRV monitoring in daily life.Scientific reports · 2024Article
- Predicting labor onset relative to the estimated date of delivery using smart ring physiological data.NPJ digital medicine · 2023Article
- Phenotyping the autonomic nervous system in pregnancy using remote sensors: potential for complication prediction.Frontiers in physiology · 2023Article
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Authors and funding
5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Despite considerable health consequences from preterm births, their incidence remains unchanged over recent decades, due partially to limited screening methods and limited use of extant methods. Wearable technology offers a novel, noninvasive, and acceptable way to track vital signs, such as maternal heart rate variability (mHRV). Previous research observed that mHRV declines throughout the first 33 weeks of gestation in term, singleton pregnancies, after which it improves. The aim of this study was to explore whether mHRV inflection is a feature of gestational age or an indication of time to delivery. This retrospective case-control study considered term and preterm deliveries. Remote data collection via non-invasive wearable technology enabled diverse participation with subjects representing 42 US states and 16 countries. Participants (N = 241) were retroactively identified from the WHOOP (Whoop, Inc.) userbase and wore WHOOP straps during singleton pregnancies between March 2021 and October 2022. Mixed effect spline models by gestational age and time until birth were fit for within-person mHRV, grouped into preterm and term births. For term pregnancies, gestational age (Akaike information criterion (AIC) = 26627.6, R2m = 0.0109, R2c = 0.8571) and weeks until birth (AIC = 26616.3, R2m = 0.0112, R2c = 0.8576) were representative of mHRV trends, with significantly stronger fit for weeks until birth (relative log-likelihood ratio = 279.5). For preterm pregnancies, gestational age (AIC = 1861.9, R2m = 0.0016, R2c = 0.8582) and time until birth (AIC = 1848.0, R2m = 0.0100, R2c = 0.8676) were representative of mHRV trends, with significantly stronger fit for weeks until birth (relative log-likelihood ratio = 859.4). This study suggests that wearable technology, such as the WHOOP strap, may provide a digital biomarker for preterm delivery by screening for changes in nighttime mHRV throughout pregnancy that could in turn alert to the need for further evaluation and intervention.
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