Non-Invasive Vital Signs Sensing: Advances, Challenges, and Future Directions in Radio Frequency Based Techniques

Global health challenges related to cardiovascular and pulmonary diseases drive the demand for more effective, non-contact methods to monitor vital signs such as heart rate (HR) and respiration rate (RR). Traditional monitoring techniques, while reliable, often rely on physical contact, limiting their utility in remote or long-term care scenarios. In this context, wireless monitoring systems leveraging radio frequency (RF) technologies, such as radar and Wi-Fi, have emerged as promising solutions for non-invasive and contactless HR and RR tracking. This paper delves into the principles and performance of state-of-the-art RF-based monitoring systems. Significant advances in signal processing techniques and machine learning (ML) models have markedly improved the accuracy and reliability of vital signs detection. These innovations underscore the potential of RF technologies to redefine healthcare monitoring. However, the adoption of RF-based systems is not without challenges. Key issues include optimizing signal processing for multiperson monitoring, mitigating interference, ensuring data security and privacy, and promoting open access to datasets. In addition, integrating edge computing and advanced ML models to enhance system intelligence and accuracy remains a critical area of research. This review provides a comprehensive understanding of the operational mechanisms underlying RF-based monitoring systems and proposes improvements to overcome current barriers, thereby advancing the field of non-invasive vital signs monitoring and broadening its application in healthcare.