Document Type : Systematic Review
Authors
MD, Obstetrician and Gynecologist Surgeon, Tehran, Iran
10.22034/jampbr.2026.604336.1131
Abstract
High-risk pregnancy requires intensive maternal and fetal surveillance, yet conventional antenatal monitoring may impose substantial travel, financial, and healthcare-system burdens. Wearable sensors, mobile health platforms, remote physiological monitoring, and artificial intelligence (AI) have emerged as technologies capable of extending pregnancy surveillance beyond the clinical setting. This systematic review synthesized evidence regarding the effects of remote maternal and fetal monitoring, particularly wearable and AI-supported technologies, on maternal and perinatal outcomes in high-risk pregnancy. Evidence identified from PubMed/MEDLINE, Embase, Web of Science, Scopus, CINAHL, Cochrane Library, and relevant reference lists, with emphasis on systematic reviews, randomized controlled trials, prospective studies, and technology evaluations. Outcomes included maternal blood pressure control, hypertensive complications, cesarean delivery, preterm birth, neonatal asphyxia, low birth weight, neonatal intensive care admission, healthcare utilization, and patient acceptability. Existing evidence indicates that remote monitoring can facilitate frequent physiological assessment, improve continuity of surveillance, and potentially reduce unnecessary face-to-face encounters. A published meta-analysis of nine studies involving 1,128 participants found a lower risk of neonatal asphyxia with remote fetal monitoring (RR = 0.66, 95% CI [0.45, 0.97]), while differences in cesarean delivery, induced labor, instrumental birth, gestational age, preterm birth, and low birth weight were not statistically significant. Recent evidence suggests that remote blood pressure monitoring in women at high risk of preeclampsia can reduce antenatal visits and hospital admissions without increasing adverse maternal or fetal outcomes. AI-based fetal heart-rate analysis may further enhance risk stratification, although external validation, interpretability, and clinical integration remain important limitations. Overall, wearable and AI-enabled remote monitoring appears promising as a complement to conventional high-risk antenatal care rather than a complete replacement for clinical assessment.
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