Real-time wireless signal processing for contactless heart rate monitoring with impulse-radio ultra-wideband radar technology

Impulse-radio ultra-wideband (IR-UWB) radar technology employs short-duration impulse waves with broad bandwidth for precise detection and tracking, offering a cost-effective, non-invasive alternative for portable heart rate monitoring. Its practical design supports long-term healthcare applications without adverse effects. However, effective implementation necessitates robust signal processing techniques to minimize interference from clutter signals and breathing harmonics, enabling the extraction of the target signal from background noise and interference. This study aims to provide real-time measurements through the implementation of signal processing algorithms such as Fast Fourier Transform (FFT), autocorrelation, and peak finding with a moving average filter (MAF) to extract heartbeat signals from background noise and interference. Algorithms were tuned for range parameters and bandpass filter order, with a Kaiser window-based FIR filter (order 250) selected for testing. The FFT algorithm achieved the highest accuracy of 85.6%, while peak finding with MAF and autocorrelation attained accuracies of 78.5% and 76.6%, respectively. The FFT algorithm demonstrated superior potential for real-time heart rate monitoring and was implemented in a graphical user interface (GUI) for data visualization.