Thesis / Research

Wireless Vital Sign Monitoring Using mmWave Radar and Phase-Based Signal Processing

A non-contact sensing research project applying FMCW radar and signal processing to estimate respiration rate and heart rate.

Problem

Conventional vital sign monitoring often requires contact sensors, electrodes or wearable devices. These can be uncomfortable, impractical or undesirable in settings where comfort, hygiene, patient movement or continuous monitoring matter.

Aim

The project investigates non-contact respiration-rate and heart-rate estimation using mmWave radar, with a focus on building a reliable single-subject proof-of-concept pipeline under controlled conditions.

Technical approach

The system is based on an Infineon BGT60 radar platform and uses FMCW radar principles to separate the target from surrounding clutter. The processing pipeline focuses on range-bin selection, phase extraction, phase unwrapping, clutter suppression, filtering and validation against reference measurements.

Tools and relevance

The work uses MATLAB and/or Python for signal processing. It is relevant to healthcare monitoring, non-contact sensing, embedded sensing, radar systems, reliable measurement pipelines and phase-based signal analysis.

Technical relevance

Why this matters technically

This project demonstrates signal-processing judgement, experimental validation, radar fundamentals, data-pipeline thinking and the ability to make complex measurements understandable and testable.

Reliable sensing

Builds a measurement pipeline where signal quality, clutter and motion artefacts must be handled carefully.

Signal processing

Uses phase-based sensing, filtering and validation to extract small physiological motion from radar data.

Engineering judgement

Balances experimental scope, hardware limitations, reference measurements and practical reliability.