I’ve begun building a vital-signs monitor around Seeed Studio’s 60 GHz mmWave radar, but I’m at the stage where deeper RF know-how and robust software are essential. The goal is clear: extract heart rate, respiratory rate, and motion data with medical-grade repeatability, then wrap those data streams so they can slot straight into the enterprise platform I already maintain. Current status • A working radar dev board from Seeed Studio is on my bench. • Basic data comes through their demo scripts, yet signal stability and range are still rough. • I have not sourced waveguide antennas or any front-end matching network. What I need from you • Identify and spec the remaining hardware: custom or off-the-shelf waveguide antennas, power supplies, shielding, whatever tightens SNR for indoor use. • Build or refine the firmware and host-side software that pulls radar IQ data, runs real-time signal processing, and outputs clear heart-rate, breath-rate, and motion metrics. Language is flexible—Python, C++, or Node.js are all fine—as long as the API you expose is REST- or MQTT-friendly for my platform. • Provide calibration procedures and a repeatable test routine so I can validate accuracy against reference devices. • Package everything so I can drop it into Docker and deploy to our edge gateway. Acceptance criteria 1. Continuous heart and respiratory rates with ≤ ±3 bpm / ±2 rpm error in a quiet room at 1 m. 2. Motion detection latency under 200 ms. 3. Clean, commented codebase and a short integration guide that targets Linux ARM64. If you’ve tuned mmWave front-ends before or pushed Seeed Studio gear beyond demo mode, let’s talk.