Digital Twin and Healthcare Research Agenda and Bibliometric Analysis

Introduction

Integrating Internet connectivity into everyday objects and technologies has substantially impacted human relationships and communications (Ramu et al., 2020). Devices may now communicate and interact via the internet and handle data remotely. IoT (Gaur et al., 2017; Gaur et al., 2021)is a term used to describe a phenomenon that is transforming how people interact with physical items and the environment. Home, health, transportation, and environmental monitoring devices are among the most recent Internet of Things innovations. Health and wellness apps that use wearable devices, in particular, have emerged as a rapidly growing sector of intelligent apps that are becoming increasingly popular. This emerging trend is expected to act as a quick and valuable resource for obtaining consumer data, which will then be used to provide healthy lifestyle recommendations. The rationale of the study is to determine the use of digital technologies like DT in their emergence and application in healthcare.

Additionally, the synergistic effect of ubiquitous connectivity, widespread sensor technologies, advances in AI, cloud computing, etc., has accelerated the spread of industrially diffused DT technology to aviation, manufacturing, and healthcare (Maddikunta et al., 2020). The DT begins the digital prototype and continues to live alongside its physical twin (PT). The DT is continually monitoring and analysing the state of its physical counterpart to optimise performance through the activation of self-optimization and self-healing processes possible through AI. The interaction between DT and PT is based on a “closed-loop,” based on data flow between the cyber and physical worlds. In healthcare, DT gets data from its PT, synchronises itself with it, employs AI algorithms to detect anomalies, and then provides the PT self-healing or optimization activities. The goal of extending DT technology to humans through the development of human DTs, which are digital models (Liu et al., 2022) of humans customised for every patient, enables clinicians to monitor the patient's health. Human DTs differ from the industry DTs generated and used in Industry 4.0; specialists are expected to update the DT regularly with PT's health status.