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Wearable devices for antenatal fetal monitoring: a systematic review

2025· article· en· W4413985600 on OpenAlexaboutno aff
Niccole Ranaei‐Zamani, Olayinka Kowobari, Dimitrios Siassakos, Sara Hillman, Anna L. David, Ilias Tachtsidis, Subhabrata Mitra

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsnot available
Fundersnot available
KeywordsWearable computerFetal monitoringElectronic fetal monitoringMedicineObstetricsComputer scienceFetusPregnancyEmbedded systemFetal heart rateBiology

Abstract

fetched live from OpenAlex

Background Stillbirth and hypoxic brain injury remain major global challenges. Conventional tools such as cardiotocography (CTG) are limited by intermittent, hospital-based use and have been linked to increased intervention without clear improvements in outcomes. Wearable devices offer portable, continuous, non-invasive monitoring that could enhance detection of fetal compromise, improve patient experience, and extend surveillance beyond hospital settings. Objectives To evaluate the effectiveness of wearable devices for antenatal fetal monitoring on maternal, fetal, and obstetric outcomes, and to map evidence on feasibility, acceptability, cost, and scalability. Search Strategy We searched Pubmed, EMBASE, Cochrane Library, and Web of Science from 2000 to July 2025. Selection Criteria Studies of wearable devices for antenatal fetal monitoring that reported fetal or maternal parameters, clinical outcomes, or acceptability were eligible. Data Collection and Analysis Two reviewers independently screened, extracted data, and assessed quality using NIH and Newcastle–Ottawa tools. Data extraction focused on clinical outcomes and acceptability; cost and scalability were captured when reported. Narrative synthesis was undertaken due to heterogeneity. Main Results Forty-one studies met inclusion criteria, spanning wearable CTG, fetal ECG, phonocardiography, photoplethysmography, near-infrared spectroscopy, and fetal movement monitors. Thirty-nine studies assessed feasibility or acceptability, which was generally high. Only two studies reported pregnancy outcomes, both showing non-inferiority of remote CTG compared with standard care. Evidence on cost and scalability was sparse. Conclusions Wearable fetal monitoring devices are feasible and acceptable but lack evidence of clinical benefit. Large, outcome-focused trials with standardised reporting of acceptability, cost, and scalability are needed to define their role in antenatal care and inform future guidelines.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.037
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.037
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.006
Bibliometrics0.0090.009
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0070.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.313
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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