Millimetre-Wave Radar for Remote Health Monitoring: Analysing Digital Biomarkers for Real-Time Insights

Elif Dogu, Janelle M. Jones, Akram Alomainy, Khalid Z. Rajab

Abstract: Millimetre-wave (mm-wave) radar sensing offers a promising IoT-enabled approach for continuous and unobtrusive health monitoring in home environments. Conventional remote monitoring methods, including wearable devices and mobile applications, often rely on user engagement, which introduces compliance, comfort, and maintenance challenges that limit their long-term utility. This paper presents an IoT-based mm-wave radar system deployed in a residential care apartment and evaluated over a six-month feasibility case study involving a single 83-year-old participant, demonstrating stable operation and real-world performance for continuous in-home monitoring. The radar nodes operate as a passive, privacy-preserving sensing infrastructure that extracts behavioural parameters and digital biomarkers such as room occupancy, movement patterns, gait speed, and activity levels without requiring user interaction. Across the deployment period, the system maintained high operational uptime (78.50%) and reliable data transmission (0.02% error), supporting uninterrupted minute-level monitoring. The system consistently captured mean daily distances moved of 38.6 m in the bedroom and 39.1 m in the living room. Gait speed distributions revealed temporal and spatial variability, with daily median speeds ranging from 0.25 to 0.55 m/s and a mean daily maximum speed of 0.78 m/s. These findings demonstrate the technical feasibility of long-term, maintenance-free operation within an IoT framework in a real-world residential setting and highlight the potential of mm-wave radar sensing for privacy-preserving, continuous in-home monitoring.

External IDs:doi:10.1109/jiot.2026.3680222