Radar-based Heartbeat Monitoring in Dynamic Scenarios
Funder: IEEE
Lead partner: UCL
Partner: Arizona State University
Lead academic: Prof Christos Masouros
Co-investigator: Dr Kawon Han
Project amount: £4,225
Research themes: Radar & RF Engineering; Bio-medical Engineering
Project period: 18 November 2024 – 15 April 2025
Project description: This proposal addresses a key challenge in radar-based health monitoring: accurately estimating average heart rate and heart rate variability (HRV) in the presence of random body movements (RBMs) in Figure 1. Traditional radar-based systems are prone to motion artifacts, limiting their effectiveness in real-world scenarios with uncontrolled movements. The proposed challenge aims to develop robust signal processing algorithms that mitigate these artifacts, allowing accurate heart rate and HRV estimation in dynamic environments. This is the first effort to implement open datasets and establish metrics for fair comparisons of motion-robustness in radar-based health monitoring systems, which have yet to be developed. Participants will estimate average heart rate and HRV, with performance evaluated using root mean square error (RMSE) and crosscorrelation metrics against reference signals. The success of this challenge will advance biomedical radar signal processing, improving the reliability and robustness of radar-based health monitoring systems. The outcomes will promote broader adoption of wireless sensing in healthcare, smart homes, automotive safety, and beyond.
