Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Aug 8;22(15):5918.
doi: 10.3390/s22155918.

Personal Digital Twin: A Close Look into the Present and a Step towards the Future of Personalised Healthcare Industry

Radhya Sahal  1 , Saeed H Alsamhi  2   3 , Kenneth N Brown  1
Affiliations

Personal Digital Twin: A Close Look into the Present and a Step towards the Future of Personalised Healthcare Industry

Radhya Sahal et al. Sensors (Basel). .

Abstract

Digital twins (DTs) play a vital role in revolutionising the healthcare industry, leading to more personalised, intelligent, and proactive healthcare. With the evolution of personalised healthcare, there is a significant need to represent a virtual replica for individuals to provide the right type of care in the right way and at the right time. Therefore, in this paper, we surveyed the concept of a personal digital twin (PDT) as an enhanced version of the DT with actionable insight capabilities. In particular, PDT can bring value to patients by enabling more accurate decision making and proper treatment selection and optimisation. Then, we explored the progression of PDT as a revolutionary technology in healthcare research and industry. However, although several research works have been performed for smart healthcare using DT, PDT is still at an early stage. Consequently, we believe that this work can be a step towards smart personalised healthcare industry by guiding the design of industrial personalised healthcare systems. Accordingly, we introduced a reference framework that empowers smart personalised healthcare using PDTs by bringing together existing advanced technologies (i.e., DT, blockchain, and AI). Then, we described some selected use cases, including the mitigation of COVID-19 contagion, COVID-19 survivor follow-up care, personalised COVID-19 medicine, personalised osteoporosis prevention, personalised cancer survivor follow-up care, and personalised nutrition. Finally, we identified further challenges to pave the PDT paradigm toward the smart personalised healthcare industry.

Keywords: COVID-19; data analysis; digital twin; personal digital twin; personalised healthcare.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Data synchronisation between the physical twin and digital twin.
Figure 2
Figure 2
Our comprehensive personal digital twin definition including mental activities, physical activities, social networks, and vital organs.
Figure 3
Figure 3
Paper structure.
Figure 4
Figure 4
Overview of the research methodology.
Figure 5
Figure 5
The high level of personal digital twin from a personalised healthcare perspective.
Figure 6
Figure 6
The benefits of using a personal digital twin.
Figure 7
Figure 7
Digital twin-based healthcare research centres and projects and their focus.
Figure 8
Figure 8
The reference framework of building PDT-based personalised healthcare systems.
Figure 9
Figure 9
The workflow of building a predictive model based on a personal digital twin.
Figure 10
Figure 10
The participants of the blockchain network include personal digital twins, healthcare authorities, healthcare industry, and operational staff participants.
Figure 11
Figure 11
Personal digital twin-based smart personalised healthcare applications areas.
Figure 12
Figure 12
The use cases of using a personal digital twin for a smart personalised healthcare industry.
Figure 13
Figure 13
PDT collaboration for mitigating COVID-19 contagion. Data are exchanged among the blockchain-based digital twins network. Arrow explanation: (a) purple arrow is for sending personal data; (b) black arrow is for sending reports to the blockchain network; (c) blue arrow is for receiving reports from the blockchain network; (d) orange arrow is for sending warnings to the cases of infection and potential infection and for sending warnings of the increase in cases to doctors, hospitals, and health organisations; (e) red arrow is for sending alerts to infected cases and for sending warnings of the increase in cases to doctors, hospitals, and health organisation; and (f) green arrow is for sending and broadcasting the decision (e.g., quarantine or lockdown) made by health organisations and governments to the blockchain network (reproduced from [26]).
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Rosen R., Von Wichert G., Lo G., Bettenhausen K.D. About the importance of autonomy and digital twins for the future of manufacturing. IFAC-PapersOnLine. 2015;48:567–572. doi: 10.1016/j.ifacol.2015.06.141. - DOI
    1. Fuller A., Fan Z., Day C., Barlow C. Digital Twin: Enabling Technologies, Challenges and Open Research. IEEE Access. 2020;8:108952–108971. doi: 10.1109/ACCESS.2020.2998358. - DOI
    1. Ringsquandl M., Lamparter S., Lepratti R., Kröger P. Knowledge Fusion of Manufacturing Operations Data Using Representation Learning; Proceedings of the IFIP International Conference on Advances in Production Management Systems; Hamburg, Germany. 3–7 September 2017; pp. 302–310.
    1. Sahal R., Alsamhi S.H., Breslin J.G., Brown K.N., Ali M.I. Digital Twins Collaboration for Automatic Erratic Operational Data Detection in Industry 4.0. Appl. Sci. 2021;11:3186. doi: 10.3390/app11073186. - DOI
    1. El Saddik A., Badawi H., Velazquez R.A.M., Laamarti F., Diaz R.G., Bagaria N., Arteaga-Falconi J.S. Dtwins: A digital twins ecosystem for health and well-being. IEEE COMSOC MMTC Commun. Front. 2019;14:39–43.