ArticleWorld journal of clinical pediatrics2026
Artificial intelligence-based neonatal heart rate monitoring technologies: Systematic review.
Article in World journal of clinical pediatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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4 authors.
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Abstract
backgroundNeonatal heart rate (HR) is an important parameter in the evaluation of newborn health and viability in the immediate postnatal period.
aimTo evaluate the accuracy, reliability, and clinical applicability of emerging non-contact and artificial intelligence (AI)-assisted HR monitoring technologies in neonates compared to conventional electrocardiography (ECG)-based systems.
methodsA comprehensive literature search was conducted across PubMed, EMBASE, Google Scholar, and Cochrane databases from January 2013 through June 2025 following PRISMA guidelines.
resultsThe analysis revealed a progressive shift from contact-based ECG and pulse oximetry to camera-based photoplethysmography, thermal imaging, and AI-enhanced multimodal systems. These newer methods demonstrated a strong correlation with ECG readings, rapid signal acquisition, and improved robustness against motion and lighting variability.
conclusionEmerging non-contact, AI-assisted HR monitoring technologies offer accurate, safe, and efficient alternatives for neonatal care, supporting faster clinical decisions and improved outcomes. Future multicenter studies are required to validate accuracy and confirm clinical utility before routine clinical implementation.
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