NICU Warmer — Intelligent Patient Monitoring#
The NICU Warmer application is a reference workload that demonstrates how multiple AI models can run simultaneously in a single GStreamer pipeline on Intel® hardware, providing real-time neonatal patient monitoring in a hospital warmer bed scenario.
It combines several AI workloads:
Object Detection (×3): Custom OpenVINO FP32 models for detecting patient presence, caretaker presence, and warmer latch clip status — all running on Intel Arc GPU.
rPPG (Remote Photoplethysmography): Contactless heart and respiratory rate estimation from facial video using MTTS-CAN, running on CPU.
Action Recognition: Kinetics-400 encoder/decoder model mapped to 11 NICU-specific activity categories, running on Intel NPU (AI Boost).
Metrics Collector: Gathers hardware and system telemetry (CPU, GPU, NPU, memory, power) from the host.
UI: Web-based React dashboard for visualizing detections, vital signs, activity, and system performance in real time.
Together, these components illustrate how vision-based AI workloads can be orchestrated across Intel GPU, NPU, and CPU, monitored, and visualized in a clinical-style scenario.
Supporting Resources#
Get Started – Step-by-step instructions to build and run the application using
makeand Docker.System Requirements – Hardware, software, and network requirements, plus an overview of the AI models used by each workload.
How It Works – High-level architecture, service responsibilities, and data/control flows.
Release Notes – Version history and known issues.
Disclaimer: This application is provided for development and evaluation purposes only and is not intended for clinical or diagnostic use.