The Multi-Modal Patient Monitoring application is a reference workload that demonstrates how multiple AI pipelines can run simultaneously on a single Intel® platform, providing consolidated monitoring for a virtual patient.
It combines several AI services:
- rPPG (Remote Photoplethysmography): Contactless heart and respiratory rate estimation from facial video.
- 3D-Pose Estimation: 3D human pose detection from video.
- AI-ECG: ECG rhythm classification from simulated ECG waveforms.
- MDPNP (Medical Device Plug-and-Play): Getting metrics of three simulated devices such as ECG, BP and CO2
- Patient Monitoring Aggregator: Central service that collects and aggregates vitals from all AI workloads.
- Metrics Collector: Gathers hardware and system telemetry (CPU, GPU, NPU, power) from the host.
- UI: Web-based dashboard for visualizing waveforms, numeric vitals, and system status.
Together, these components illustrate how vision- and signal-based AI workloads can be orchestrated, monitored, and visualized in a clinical-style scenario.
- 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.
Disclaimer: This application is provided for development and evaluation purposes only and is not intended for clinical or diagnostic use.