Research on Vital Signs Monitoring Technology Based on Wireless Sensing

Abstract

Vital signs monitoring serves as a critical means of assessing human health, yet traditional contact-based devices suffer from issues such as poor comfort and potential allergenicity. Contactless monitoring technology utilising Wi-Fi signals has emerged as a significant avenue for overcoming these limitations, owing to its widespread availability, penetration capabilities, and low-cost advantages. This paper systematically investigates core methodologies, application scenarios, and technical bottlenecks of wireless sensing technologies for respiratory and heart rate monitoring. The study first compares two primary respiratory monitoring techniques: CSI complex-domain signal processing and CSI ratio trajectory analysis. It also examines two key heart rate monitoring approaches: end-to-end CNN learning and rotary projection combined with HSR subcarrier selection. Results indicate that the current optimal solution achieves respiratory errors below 0.5 BPM and median heart rate errors of 0.8 BPM in static scenarios, significantly outperforming baseline methods. The study further explores the technology's suitability across four key application domains—medical monitoring, sleep assessment, home-based elderly care, and in-vehicle safety—validating its cross-scenario potential. Existing bottlenecks are identified as environmental interference, insufficient dynamic robustness, individual variability, and multi-object separation challenges. Future breakthroughs require collaborative efforts in multimodal sensor fusion, lightweight algorithms, and clinical integration. This technology pioneers a new paradigm for contactless, continuous, and all-scenario vital signs monitoring, extending health management beyond clinical settings into daily life and laying the technological foundation for building a proactive health society.