# VitalMonitor RS: Contactless Microwave Radar Vital Signs

> Rewriting a legacy Python medical radar workstation into a hardware-accelerated Rust, GPUI, and ONNX real-time telemetry system.

- Client: Confidential
- Year: 2025
- Disciplines: Rust, GPUI, ONNX Runtime, Digital Signal Processing, Embedded & Medical IoT
- Page: https://ponkster.me/case-studies/vital-monitor-rs
- Studio: ponkster.me (https://ponkster.me)
- Contact: origin.ponkster@gmail.com

## Challenge

The original Python desktop application for contactless microwave radar vital-sign monitoring struggled with UI frame drops, GIL contention, and packaging fragility when processing real-time IQ radar streams alongside CNN inference.

## Approach

We executed a complete Rust rewrite organized as a multi-crate workspace combining bandpass DSP filtering, FFT frequency analysis, envelope detection, and dynamically loaded ONNX Runtime CNN models for heart-rate (40-120 BPM), breathing-rate (10-30 BPM), and patient-state classification, rendered at 60fps in Zed's GPUI framework.

## Outcome

Replaced a fragile Python runtime with a deterministic native binary capable of real-time multi-algorithm fusion and synthetic IQ sensor simulation without hardware attached.

## Results

- Complete Rust + GPUI rewrite of the legacy Python radar monitoring suite
- Multi-algorithm fusion combining FFT, envelope detection, and ONNX CNN inference
- Built-in synthetic IQ radar waveform generator for hardware-free validation

## Optional

- [Studio overview and all case studies](https://ponkster.me/llms.txt)