Digital Twin Empowered Wireless Healthcare Monitoring for Smart Home
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 real...
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Published in | IEEE Journal on Selected Areas in Communications Vol. 41; no. 11; p. 1 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English Japanese |
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New York
IEEE
01.11.2023
Institute of Electrical and Electronics Engineers (IEEE) The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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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. |
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AbstractList | 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. |
Author | Leung, Victor C. M. Chen, Junxin Liu, Yu Wang, Wei Hu, Xiping Yu, Keping Fang, Bo |
Author_xml | – sequence: 1 givenname: Junxin orcidid: 0000-0003-4745-8361 surname: Chen fullname: Chen, Junxin organization: School of Software, Dalian University of Technology, Dalian, China – sequence: 2 givenname: Wei orcidid: 0000-0002-1717-5785 surname: Wang fullname: Wang, Wei organization: Department of Engineering, Shenzhen MSU-BIT University, Shenzhen, China – sequence: 3 givenname: Bo surname: Fang fullname: Fang, Bo organization: College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China – sequence: 4 givenname: Yu surname: Liu fullname: Liu, Yu organization: College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China – sequence: 5 givenname: Keping orcidid: 0000-0001-5735-2507 surname: Yu fullname: Yu, Keping organization: Graduate School of Science and Engineering, Hosei University, Tokyo, Japan – sequence: 6 givenname: Victor C. M. orcidid: 0000-0003-3529-2640 surname: Leung fullname: Leung, Victor C. M. organization: College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China – sequence: 7 givenname: Xiping surname: Hu fullname: Hu, Xiping organization: Department of Engineering, Shenzhen MSU-BIT University, Shenzhen, China |
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SubjectTerms | Algorithms Artificial intelligence Biomedical monitoring Cloud computing Digital twin Digital twins Electrocardiography Fall detection Health care Healthcare monitoring Houses Medical services Monitoring Real time Smart buildings Smart home Smart homes Smart houses Telemedicine Visualization Wearable computers Wearable technology |
Title | Digital Twin Empowered Wireless Healthcare Monitoring for Smart Home |
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