Exploiting Wireless Communication Using Software-defined Radio Frequency Sensing For E-health APPLICATIONS

Abstract

E-Health applications have recently become a popular topic in academia and industry. E-health has improved several key aspects of conventional healthcare paradigms due to its interdisciplinary approach. Furthermore, it facilitates an easier connection between the patient and the hospital, allowing E-health-based applications and public services to be accessed more efficiently. How-ever, the current reliance of E-health services on invasive sensing systems has been attributed to rising diseases, pandemics, costs, and well-being. Non-invasive sensing was selected as a possible solution to this problem because of its innate ability to improve containment, comfortability, privacy protection, and efficiency. Existing non-invasive sensing research studies exploit wireless communication systems having portability, adaptability, and flexibility issues for large-scale implementation to provide cost-effective, intelligent health-care services. This article discusses non-invasive sensing challenges for E-health applications using wireless communication systems, and proposes a software-defined radio frequency (SDRF) sensing system. The integration of advanced signal processing (SP) and artificial intelligence (AI) techniques with SDRF sensing systems has the potential to overcome the challenges of existing wireless communication-based systems and meet the demands of massive E-Health applications.