Digital twin and sensor networks for healthcare monitoring frameworks

Digital twins (DTs) have emerged as a groundbreaking development in digital technology, providing intricate digital representations of physical entities for remote, real-time monitoring and analysis. This paper provides a survey based on the existing DT literature in the healthcare domain. We outline the key DT attributes and investigate the contemporary domains where its applications are progressing within the healthcare domain, including recent advancements in sensor technology that facilitate affordable health monitoring. The literature of different domains including AI and sensor networks is reviewed to investigate their roles in implementing DT applications in the healthcare domain. Covering the period 2015−23, the study analyzes numerous papers and case studies that use DT to manage chronic diseases, such as diabetes and neurological disorders. The study concludes by identifying key challenges and potential areas for future research in this domain. These directions could guide researchers in the future to enhance the literature on DT in the medical domain.