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

Najah Abuali, Muhammad Bilal Khan, Mohammad Hayajneh, Mubashir Rehman

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)42-48
Number of pages7
JournalIEEE Communications Standards Magazine
Issue number4
Publication statusPublished - Dec 1 2023

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Computer Networks and Communications
  • Law
  • Management of Technology and Innovation


Dive into the research topics of 'Exploiting Wireless Communication Using Software-defined Radio Frequency Sensing For E-health APPLICATIONS'. Together they form a unique fingerprint.

Cite this