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Sensor-Enabled Digital Twins for Healthcare Applications: Unlocking Their Potential

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (30 March 2024) | Viewed by 572

Special Issue Editors


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Guest Editor
Professor & Optus Chair of Digital Health, School of Computing, Engineering and Mathematical Sciences, La Trobe University, Melbourne, VIC 3086, Australia
Interests: digital health applications

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Guest Editor
Researcher & Member of the Optus Chair Digital Health Team, School of Computing, Engineering and Mathematical Sciences, La Trobe University, Melbourne, VIC 3086, Australia
Interests: mathematical modeling; digital health; sensors and applications

Special Issue Information

Dear Colleagues,

Digital twins are digital replications of whole or partial aspects of physical entities. The purpose of these twins is to connect with the physical entities through sensors and data transfer mechanisms to simulate the physical entities’ activities. Using information about the present and past states of these entities, their future progression can be forecasted. These forecasts can then be used to support decision-making at present in order to drive the physical entities to desired or optimal future states. This approach has been the classical underlying principle of model-based control engineering for several decades. The rapid advancements in sensor technologies have widened the applications of digital twins in healthcare, transforming sectors such as genomics, aged care, cancer care, dementia, and more. This Special Issue is a forum that invites the latest developments in such digital twin applications for healthcare. This Special Issue will cover healthcare-related topics including, but not limited to:

  • Implementation of digital twins in healthcare, evidence and lessons learnt.
  • Sensor technologies and their implementation in digital twins for healthcare.
  • Role of sensors in digital twins for smart hospitals and remote care.
  • Digital twins in care delivery (e.g., robotic surgery, robotic drug deliver, prosthetics, and control).
  • Sensor applications for precision and personalization of care using digital twins.
  • Disease progression modeling using sensor data in digital twins.

Since digital twins in healthcare is an emerging area, completed research works with evidence, as well as work in progress papers with adequate evidence, will be considered. In addition, well-rationalized concepts and vision papers about the future will also be considered. However, systematic literature reviews and/or scoping reviews are only likely to be acceptable if of a very high standard.

Prof. Dr. Nilmini Wickramasinghe
Dr. Nalika Ulapane
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • digital twins
  • sensors and applications
  • IoT
  • smart hospital
  • care delivery
  • remote care
  • robotic surgery
  • robotic drug delivery
  • prosthetics
  • precision healthcare
  • personalization of care

Published Papers (1 paper)

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Review

32 pages, 865 KiB  
Review
Enhancing Healthcare through Sensor-Enabled Digital Twins in Smart Environments: A Comprehensive Analysis
by Sasan Adibi, Abbas Rajabifard, Davood Shojaei and Nilmini Wickramasinghe
Sensors 2024, 24(9), 2793; https://doi.org/10.3390/s24092793 (registering DOI) - 27 Apr 2024
Viewed by 126
Abstract
This comprehensive review investigates the transformative potential of sensor-driven digital twin technology in enhancing healthcare delivery within smart environments. We explore the integration of smart environments with sensor technologies, digital health capabilities, and location-based services, focusing on their impacts on healthcare objectives and [...] Read more.
This comprehensive review investigates the transformative potential of sensor-driven digital twin technology in enhancing healthcare delivery within smart environments. We explore the integration of smart environments with sensor technologies, digital health capabilities, and location-based services, focusing on their impacts on healthcare objectives and outcomes. This work analyzes the foundational technologies, encompassing the Internet of Things (IoT), Internet of Medical Things (IoMT), machine learning (ML, and artificial intelligence (AI), that underpin the functionalities within smart environments. We also examine the unique characteristics of smart homes and smart hospitals, highlighting their potential to revolutionize healthcare delivery through remote patient monitoring, telemedicine, and real-time data sharing. The review presents a novel solution framework leveraging sensor-driven digital twins to address both healthcare needs and user requirements. This framework incorporates wearable health devices, AI-driven health analytics, and a proof-of-concept digital twin application. Furthermore, we explore the role of location-based services (LBS) in smart environments, emphasizing their potential to enhance personalized healthcare interventions and emergency response capabilities. By analyzing the technical advancements in sensor technologies and digital twin applications, this review contributes valuable insights to the evolving landscape of smart environments for healthcare. We identify the opportunities and challenges associated with this emerging field and highlight the need for further research to fully realize its potential to improve healthcare delivery and patient well-being. Full article
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