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A Novel Cloud-Based Framework for the Elderly Healthcare Services Using Digital Twin

  • Ying Liu
  • , Lin Zhang*
  • , Yuan Yang
  • , Longfei Zhou
  • , Lei Ren
  • , Fei Wang
  • , Rong Liu
  • , Zhibo Pang
  • , M. Jamal Deen
  • *此作品的通讯作者
  • Beihang University
  • General Hospital of People's Liberation Army
  • ABB Group
  • McMaster University

科研成果: 期刊稿件文章同行评审

摘要

With the development of technologies, such as big data, cloud computing, and the Internet of Things (IoT), digital twin is being applied in industry as a precision simulation technology from concept to practice. Further, simulation plays a very important role in the healthcare field, especially in research on medical pathway planning, medical resource allocation, medical activity prediction, etc. By combining digital twin and healthcare, there will be a new and efficient way to provide more accurate and fast services for elderly healthcare. However, how to achieve personal health management throughout the entire lifecycle of elderly patients, and how to converge the medical physical world and the virtual world to realize real smart healthcare, are still two key challenges in the era of precision medicine. In this paper, a framework of the cloud healthcare system is proposed based on digital twin healthcare (CloudDTH). This is a novel, generalized, and extensible framework in the cloud environment for monitoring, diagnosing and predicting aspects of the health of individuals using, for example, wearable medical devices, toward the goal of personal health management, especially for the elderly. CloudDTH aims to achieve interaction and convergence between medical physical and virtual spaces. Accordingly, a novel concept of digital twin healthcare (DTH) is proposed and discussed, and a DTH model is implemented. Next, a reference framework of CloudDTH based on DTH is constructed, and its key enabling technologies are explored. Finally, the feasibility of some application scenarios and a case study for real-time supervision are demonstrated.

源语言英语
文章编号6287639
页(从-至)49088-49101
页数14
期刊IEEE Access
7
DOI
出版状态已出版 - 2019

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