Confidence-Aware Real-Time Neonatal Monitoring with Intelligent False Alarm Suppression and Trend Analysis

This paper has presented the design, implementation, and evaluation of Vetra, a confidence-aware neonatal monitoring system that addresses the critical problem of alarm fatigue in intensive care environments. Through a multi-variate Sig- nal Confidence Engine, a deterministic Neonatal Risk Score, and intelligent alert suppression logic, the system achieves a 100% reduction in artifact-induced false critical alarms while maintaining zero detection latency for genuine physiological deterioration. The hardware architecture, based on the ESP32-WROOM- 32 with MAX30100, AD8232, MAX30205, and MPU6050 sensors, provides a cost-effective, wireless-enabled monitoring platform suitable for deployment in resource-limited health- care settings. The software architecture implements a com- plete processing pipeline from raw sensor data to explainable clinical alerts, with all computation performed on-device. The evaluation across five clinically representative scenarios demonstrates that the confidence-aware approach provides a principled and effective solution to the false alarm problem. By shifting the paradigm from threshold crossing to contextual risk assessment, Vetra represents a meaningful step toward more intelligent and reliable neonatal monitoring systems that can maintain clinician trust and enhance patient safety.

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