Subhatharani

Subhatharani / neon-icu-vitals-monitor

Public

Real-time vitals monitoring system with neon ICU dashboard

54
0
69% credibility
Found Feb 05, 2026 at 52 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Jupyter Notebook
AI Summary

This project simulates lifelike streams of patient vital signs for various profiles, checks them against personalized normal ranges using rules and predictive models, and shows live graphs with alerts on a simple screen for healthcare demos.

How It Works

1
🩺 Discover the demo tool

You find this handy simulator for fake patient vitals while searching for ideas to demo ICU monitoring in a class or hackathon.

2
📥 Get everything ready

Download the pieces to your computer so you can generate patient data, check for problems, and watch it all on a screen.

3
🚀 Pick a patient and start vitals

Choose a type like adult or child, then turn on the generator to create ongoing realistic heartbeats, oxygen levels, blood pressure, and temperature.

4
🔍 Activate the safety checker

Connect the smart watcher that learns each patient's normal ranges and spots any dangerous changes right away.

5
📊 Open the live dashboard

Bring up the screen showing real-time vital signs updating every few seconds with color alerts if anything looks wrong.

🎉 Your demo is alive!

Watch as the system catches fake emergencies and flashes warnings, just like a real hospital monitor, ready for your presentation.

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Star Growth

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AI-Generated Review

What is neon-icu-vitals-monitor?

This Jupyter Notebook project simulates real-time vitals like heart rate, SpO2, blood pressure, and temperature for neon ICU patients, using personalized baselines to detect outliers via rules and ML models. It feeds data through a FastAPI endpoint for analysis and alerting, then displays live streams and warnings on a Streamlit dashboard. Developers get a full real-time vitals monitoring system for prototyping without needing real sensors or patient data.

Why is it gaining traction?

Its hook is the mix of realistic patient profiles—normal adults, hypertensives, kids—with hybrid detection that flags deviations relative to individual baselines, plus instant alerts on a polling dashboard. Unlike basic simulators, it includes pre-trained risk models for probabilistic scoring, making real-time ICU demos feel clinical. At 54 stars, it appeals for quick real-time projects on GitHub, especially hackathons needing a ready real-time dashboard.

Who should use this?

Healthcare devs prototyping remote monitoring or IoT systems, academic researchers validating anomaly detection in vitals streams, and hackathon teams building neon ICU dashboards. It's for those tired of fabricating test data manually and wanting a real-time API GitHub starter for clinical alerting.

Verdict

Grab it for demos or learning—solid README docs and easy local setup make it practical despite 54 stars and a 0.7% credibility score signaling early maturity. Skip for production until sensor integration and tests land.

(178 words)

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