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Health·The Trace·Dual reading·Published 2026-09-09

AI-assisted non-contact heart rate monitoring for neonates compared to ECG

Source article: Artificial intelligence-based neonatal heart rate monitoring technologies: Systematic review

Abstract: Background Neonatal heart rate (HR) is an important parameter in the evaluation of newborn health and viability in the immediate postnatal period. Aim To 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. Methods A comprehensive literature search was conducted across PubMed, EMBASE, Google Scholar, and Cochrane databases from Januar…

TRV-2026-1024Peer-reviewedPermanent record — cite & verify
Trace impact reading

Contested: both sides are scored from claims and sources, not community votes.

P 69The P score combines the specificity and measured human impact of the grounded problem claim with the strength of this Trace’s cited sources.G 71The G score combines the specificity and measured human impact of the grounded gain claim with the strength of this Trace’s cited sources.
Artificial intelligence-based neonatal heart rate monitoring technologies: Systematic review

Non-contact respiration monitoring using impulse radio ultrawideband radar in neonates by Kim, Jong Deok; Lee, Won Hyuk; Lee, Yonggu; Lee, Hyun Ju; Cha, Teahyen; Kim, Seung Hyun; Song, Ki-Min; Lim, Young-Hyo; Cho, Seok Hyun; Cho, Sung Ho; Park, Hyun-Kyung. CC BY 4.0 · https://creativecommons.org/licenses/by/4.0

The quick read

A systematic review covering January 2013 to June 2025 examined non-contact and AI-assisted neonatal heart rate monitoring versus conventional ECG. It found a progressive shift toward camera-based photoplethysmography, thermal imaging, and AI-enhanced multimodal systems that showed strong correlation with ECG, rapid acquisition, and better robustness to motion and lighting.

For neonatal care, non-contact AI methods could reduce contact-related risks and enable faster viability assessment in the immediate postnatal period. As of the September 2026 publication date, the review positions these as promising alternatives but explicitly conditions routine use on future multicenter validation of accuracy and clinical utility.

Main points
  • Systematic review searched PubMed, EMBASE, Google Scholar, and Cochrane from January 2013 through June 2025 following PRISMA guidelines.
  • Review documents shift from contact-based ECG and pulse oximetry to camera-based photoplethysmography, thermal imaging, and AI-enhanced multimodal systems.
  • Newer methods reported improved robustness against motion and lighting variability compared to conventional systems.
Gain

AI-assisted non-contact heart rate monitoring provides accurate, safe, and efficient neonatal assessment with strong correlation to ECG and rapid signal acquisition.

Problem

Accuracy and clinical utility of AI-assisted non-contact neonatal heart rate monitoring remain unvalidated for routine implementation pending future multicenter studies.

The rundown

The review evaluated accuracy, reliability, and clinical applicability of emerging non-contact and AI-assisted heart rate monitoring technologies in neonates compared to conventional electrocardiography-based systems.

Authors searched four databases over a 12.5-year window and concluded these technologies support faster clinical decisions while noting validation gaps before routine adoption in immediate postnatal care.

Sources

Reader signal

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The debate