Introduction to the Special Issue on Wireless Sensing for Health Monitoring and Elderly Care
Résumé
Wireless sensing for health is an emerging paradigm that has drawn significant attention recently. It leverages signals from widely available wireless communication technologies, such as WiFi, mmWave, and RFID, to provide powerful sensing capabilities for healthcare monitoring tasks. This innovative approach enables continuous and contactless health monitoring, utilizing RF signals to support applications like heart rate monitoring, breathing rate tracking, sleep analysis, daily behavior monitoring, and fitness assessments. The evolution of wireless sensing for health has progressed from single-point, coarse-grained measurements (e.g., single data streams and received signal strength) to more sophisticated, multi-dimensional data (e.g., multiple data streams and channel state information). Unlike traditional sensor-based systems, wireless health sensing does not require users to wear or carry devices, allowing for unobtrusive, seamless monitoring of health metrics in various environments, from homes to clinical settings, without the need for direct user interaction.
Wireless health sensing enables a broad range of contactless monitoring applications, each with significant impacts on healthcare and personal wellbeing. For example, physiological signal monitoring technologies like WiFi, mmWave, and RFID facilitate continuous, real-time tracking of vital signs such as heart and breathing rates. Such technologies allow for early health issue detection, personalized treatment plans, and proactive health management. It is particularly impactful in clinical and eldercare settings where uninterrupted monitoring enhances patient safety and quality of care. Another wireless health sensing application is daily behavior monitoring, which captures patterns in everyday activities. This technology offers comprehensive insights into behavioral changes that might indicate health concerns, such as falling, reduced mobility, or irregular routines. Such information is beneficial for chronic disease management, as it enables caregivers and healthcare providers to monitor and respond to changes in a patient's routine non-intrusively. Furthermore, wireless sensing-based sleep monitoring systems can unobtrusively track sleep patterns and behaviors, analyzing movement and physiological indicators throughout the night. Patients and doctors can obtain insights into sleep quality and identify sleep disorders without wearing dedicated sensors that could disrupt natural sleep. Finally, fitness tracking leverages wireless sensing to accurately track physical activity levels and exercise patterns. With advanced AI technologies, such systems can support users in managing their fitness goals and maintaining active lifestyles without hiring expensive professional trainers.
Domaines
Informatique [cs]Origine | Fichiers produits par l'(les) auteur(s) |
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