Dalarna University's logo and link to the university's website

du.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • chicago-author-date
  • chicago-note-bibliography
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
A Systematic Review of Digital Twin Technology for Home Care
Dalarna University, School of Information and Engineering, Microdata Analysis.ORCID iD: 0000-0002-7223-7977
Dalarna University, School of Information and Engineering, Microdata Analysis.ORCID iD: 0000-0002-3650-9162
Dalarna University, School of Health and Welfare, Medical Science.ORCID iD: 0000-0003-4432-5256
2024 (English)In: ACM Transactions on Computing for Healthcare, E-ISSN 2637-8051, Vol. 5, no 4, article id 20Article in journal (Refereed) Published
Abstract [en]

The concept of digital twin has captured significant attention in recent years and its potential application within the domain of home care has been explored in several studies. This review endeavors to provide a comprehensive overview of digital twin technology and its applications in the realm of home care, delineating the key attributes and challenges entailed in their implementation. A systematic search was conducted across five databases, namely ACM digital library, IEEE Xplore, PubMed, Scopus, and Web of Science. Findings from forty-five included articles were categorized employing a systematic approach, highlighting the technology’s deployment in remote older adults’ care monitoring, health issue prediction and personalized treatment planning. Furthermore, this review identified challenges of integrating digital twins into the home care sector. Despite recognition of its potential, there is a distinct lack in the literature of in-depth studies specifically exploring the implementation of digital twin technology in home care, highlighting the need for further research.

Place, publisher, year, edition, pages
2024. Vol. 5, no 4, article id 20
Keywords [en]
Human Activity Recognition, Social Care, Cloud Computing, Physiological Signals, Human-Computer Interaction (HCI)
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:du-49208DOI: 10.1145/3681797ISI: 001372531000001Scopus ID: 2-s2.0-85210764094OAI: oai:DiVA.org:du-49208DiVA, id: diva2:1887213
Available from: 2024-08-07 Created: 2024-08-07 Last updated: 2024-12-20Bibliographically approved

Open Access in DiVA

fulltext(41897 kB)59 downloads
File information
File name FULLTEXT01.pdfFile size 41897 kBChecksum SHA-512
f39174294c93a69d034c2b33f464503e5dafae9b8cf22b4b6aa2b3276adc615a0ffedc627f641e0f07327b462ebe2dad8847cf4a60b45f6d8895ccc81b23ec1f
Type fulltextMimetype application/pdf

Other links

Publisher's full textScopus

Authority records

Zafar, Raja OmmanRybarczyk, YvesBorg, Johan

Search in DiVA

By author/editor
Zafar, Raja OmmanRybarczyk, YvesBorg, Johan
By organisation
Microdata AnalysisMedical Science
Computer and Information Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 59 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 132 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • chicago-author-date
  • chicago-note-bibliography
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf