Edge Computing Empowered Tactile Internet for Human Digital Twin: Visions and Case Study

A case study of ECoTI for HDT in physical therapy.


Tactile Internet (TI), with the capability of providing multisensory haptic human-machine interactions, is envisioned as a key enabling technology for an emerging application, called human digital twin (HDT). HDT is expected to revolutionize the human lifestyle and prompts the development of Metaverse. However, the realization of HDT poses stringent demands on pervasive connectivity, real-time feedback, high-fidelity modeling and ultra-high reliability (between physical and virtual spaces), which can hardly be met by TI only. In this article, we thus shed light on the design of edge computing empowered TI (ECoTI) for HDT. Aiming at offering strong interactions and extremely immersive quality of experience, we introduce the system architecture of ECoTI for HDT, and analyze its major design requirements and challenges. Moreover, we present core guidelines and detailed steps for system implementations. In addition, we conduct an experimental study based on our recently built testbed, which shows a particular use case of ECoTI for HDT in physical therapy, and the results indicate that the proposed framework, i.e., ECoTI, can significantly improve the effectiveness of the system. Finally, we conclude this article with a brief discussion of open issues and future directions.


Here is our Edge Computing empowered Tactile Internet (ECoTI) in Physical Therapy Testbed Demo Video.

This magazine paper has been submitted to IEEE Network on 15 April, 2023, and is currently under review. Due to the long review cycle, it has also been uploaded to arXiv. You can download the paper by clicking on the arXiv button or directly through the PDF button above.
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Jiayuan Chen
Jiayuan Chen
PhD Candidate in Computer Science and Technology

My research interests include Human Digital Twin (HDT), Network Resource Management, Edge Computing and Edge Intelligence, Tactile Internet (TI), and Data-Driven Optimization and Learning.