Evidence mapPaperPMID 41530894Full record

ReviewSleep2026

Fetal sleep: a cross-species review of physiology, measurement, and classification.

Weitao Tang, Johann Vargas-Calixto, Nasim Katebi, Robert Galinsky, Gari D Clifford, Faezeh Marzbanrad

Abstract readReview
In one paragraph

Review in Sleep, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Weitao TangDepartment of Electrical and Computer Systems Engineering, Monash University, Melbourne, Australia.ORCID 0009-0000-9228-7771
Johann Vargas-CalixtoDepartment of Biomedical Informatics, Emory University, Atlanta, GA, United States.ORCID 0000-0002-4886-353X
Nasim KatebiDepartment of Biomedical Informatics, Emory University, Atlanta, GA, United States.
Robert GalinskyThe Ritchie Centre, Hudson Institute of Medical Research, Melbourne, Australia.ORCID 0000-0002-6374-9372
Gari D CliffordDepartment of Biomedical Informatics, Emory University, Atlanta, GA, United States.
Faezeh MarzbanradDepartment of Electrical and Computer Systems Engineering, Monash University, Melbourne, Australia.

Funding

AI-driven low-cost ultrasound for automated quantification of hypertension, preeclampsia, and IUGRR01HD110480 · EMORY UNIVERSITY · 2025 to 2025
$611k
Cerebral Palsy Alliance Fellowship ERG02123Google.org AI for the Global Goals Impact ChallengeNHMRC 1124493NHMRC 1164954NICHD NIH HHS R01 HD110480NIH HHS R01HD110480PREHS-SEED K12ES033593
6 · The paper itself

Abstract

STUDY

objectivesFetal sleep is a vital yet underexplored aspect of prenatal neurodevelopment. Its cyclic organization reflects the maturation of central neural circuits, and disturbances in these patterns may offer some of the earliest detectable signs of neurological compromise. This is the first review to integrate more than seven decades of research into a unified, cross-species synthesis of fetal sleep. We examine: (1) Physiology and Ontogeny-comparing human fetuses with animal models; and (2) Methodological Evolution-transitioning from invasive neurophysiology to non-invasive monitoring and deep learning frameworks.

methodsA structured narrative synthesis was guided by a systematic literature search across four databases (PubMed, Scopus, IEEE Xplore, and Google Scholar). From 2925 identified records, 169 studies involving fetal sleep-related physiology, sleep-state classification, or signal-based monitoring were included in this review.

resultsAcross the 169 studies, fetal sleep states become clearly observable as the brain matures. In fetal sheep and baboons, organized cycling between active and quiet sleep emerges at approximately 80%-90% gestation. In humans, this differentiation occurs later, around 95% gestation, with full maturation reached near term. Despite extensive animal research, no unified, clinically validated framework exists for defining fetal sleep states, limiting translation into routine obstetric practice.

conclusionsBy integrating evidence across species, methodologies, and clinical contexts, this review provides the scientific foundation for developing objective, multimodal, and non-invasive fetal sleep monitoring technologies-tools that may ultimately support earlier detection of neurological compromise and guide timely prenatal intervention.

Indexed as

FetusSleepAnimalsBrainFemaleHumansPregnancySheepSpecies Specificityfetal behavioral statesfetal monitoringfetal sleepneurodevelopmentsleep classification

Identifiers

PMID41530894
PMCPMC13089461

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.