Neonatal World Conference 2026

Abstract

Background:
Current neonatal monitoring systems are primarily derived from adult medical devices through geometric scaling and miniaturization. While this enables placement in neonatal intensive care settings, it does not sufficiently account for fundamental physiological differences between adults and neonates. Neonates have immature and highly permeable skin, rapidly changing tissue impedance, non-linear cardiopulmonary dynamics, and increased susceptibility to motion artifacts. These factors contribute to reduced signal reliability and persistent restrictions in clinical reliability.

Objective:
To define a paradigm change in neonatal sensor design from adult-based miniaturization toward a physiology-first innovation framework.

Methods:
A conceptual framework based on neonatal physiological constraints and limitations of adult-derived sensor architectures is presented. The framework focuses on neonatal-specific design principles including physiology-aligned signal acquisition, adaptive artifact suppression in motion-rich environments, and interface design optimized for fragile neonatal skin–device interaction. The approach emphasizes system design based on neonatal biological characteristics rather than adaptation of adult technologies.

Conceptual Findings:
The miniaturization approach assumes linear scalability of adult sensing systems, which is not applicable to neonatal physiology. Neonatal biological signals are dynamic, rapidly evolving, and non-linear. A physiology-first design approach improves alignment between sensor systems and biological conditions. It has the potential to enhance signal quality, reduce motion artifacts, and improve clinical interpretability of neonatal monitoring data. This represents a shift from size-based scaling to biologically grounded system design.

Conclusion:
Neonatal Sensor Design must move beyond adult-based miniaturization toward a physiology-first innovation framework. This approach supports the development of monitoring systems aligned with neonatal life and may improve accuracy, reliability, and clinical relevance in neonatal care settings.