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In-Home Monitoring Using Wireless on the Walls for Future HealthCare: Real-World Demonstration

  • Jalil ur Rehman Kazim
  • , Ahsen Tahir
  • , James Rains
  • , Tie Jun Cui
  • , Abdul Jabbar
  • , Muhammad Ali Jamshed
  • , Masood Ur-Rehman
  • , Akram Alomainy
  • , Muhammad Ali Imran
  • , Qammer H. Abbasi
  • University of Glasgow
  • University of Engineering and Technology Lahore
  • Southeast University, Nanjing
  • Queen Mary University of London

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Since the last decade radio frequency (RF) sensing has emerged as an alternative in-home monitoring and tracking technology because of its inherent device-free and privacy-preserved features over camera and wearable technologies. In this work, contrary to conventional radar-based sensing and WiFi-based setups which require line-of-sight (LoS) to process and collect the RF signals for monitoring, it is shown for the first time in literature the potential of using RF sensing for vitals, that is, heartbeat detection in the non-line-of-sight (NLoS) using an in-house-developed reconfigurable intelligent surface (RIS), that is, wireless on the walls. The developed RIS is the world's first prototype which consists of “4096 elements”. The unit cell elements are individually controlled via PIN diodes, 1-bit, operating at 3.75 GHz specified for the fifth-generation (5G) network. Near-field beam steering is demonstrated, with a switching speed of 15 ms. For the first time in the literature its is demonstrated that RIS can assist in the detection of microactivities including the human heartbeat in NLoS indoor complex environment, a limitation with the existing RF sensing technologies to date. In addition, it is experimentally verified that the RIS can potentially reduce the e-field magnitude at the user's by regulating the gain at the user terminal.

Original languageEnglish
Article number2300007
JournalAdvanced Intelligent Systems
Volume5
Issue number9
DOIs
StatePublished - Sep 2023
Externally publishedYes

Keywords

  • healthcare
  • intelligent reflect surfaces
  • radio frequency sensing
  • specific absorption rates

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