Digital Twin Empowered Wireless Healthcare Monitoring for Smart Home

Junxin Chen, Wei Wang*, Bo Fang, Yu Liu, Keping Yu, Victor C.M. Leung, Xiping Hu*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

33 Citations (Scopus)

Abstract

The dramatic progresses of wireless technologies and wearable devices have significantly promoted the development and popularity of smart home, while digital twin (DT) emerges as a game changer benefiting from its enhanced capabilities of visualization and interaction. The DT is able to build a realtime and continuous visual replica of a physical object or process, and to provide realtime monitoring, anomaly prediction, smart interaction, and lifecycle management. This paper presents a DT model to empower healthcare monitoring in the smart home with the goals of graphical monitoring, healthcare prediction, and intelligent control. High fidelity DT of the house and its equipments is created for visualized monitoring, and two suites of devices are deployed for continuously acquiring the users' electrocardiograph (ECG) waves and the WiFi signals in the house. Two intelligent algorithms are then developed to perform fall detection from WiFi signals and to screen atrial fibrillation from ECG waves collected by wearable devices. Experimental results well validate the proposed model's effectiveness for smart home monitoring, and the advantages of the developed smart algorithms for healthcare prediction over counterparts.

Original languageEnglish
Pages (from-to)3662-3676
Number of pages15
JournalIEEE Journal on Selected Areas in Communications
Volume41
Issue number11
DOIs
Publication statusPublished - 1 Nov 2023

Keywords

  • Digital twin
  • artificial intelligence
  • healthcare monitoring
  • smart home

Fingerprint

Dive into the research topics of 'Digital Twin Empowered Wireless Healthcare Monitoring for Smart Home'. Together they form a unique fingerprint.

Cite this