ReviewFrontiers in robotics and AI2026
Human-centric digital twins in industry 5.0: technologies, applications, and future directions.
Review in Frontiers in robotics and AI, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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6 authors.
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Abstract
Industry 5.0 (I5.0) emphasizes industrial technologies that are human-centric, sustainable, and resilient. Human-Centric Digital Twins (HCDTs) support this transition by integrating worker data with robots, machines, tasks, and industrial environments. However, the relevant research remains fragmented across human modelling, Human-Robot Collaboration, Artificial Intelligence (AI), simulation, and Digital Twin (DT) research. Moreover, systems that use human data or adaptive automation are often described as human-centric without demonstrating measurable benefits to workers. This review addresses these limitations by distinguishing HCDTs from conventional human models, Human DTs, and collaborative robotic systems. It critically examines human-focused sensing, multi-modal data integration, biomechanical modelling, intention and motion prediction, robotic simulation, optimization, reinforcement learning, immersive interfaces, industrial connectivity, and data governance. Based on this analysis, a literature-derived conceptual framework is proposed that connects sensing, integration, human modelling, analytics, simulation, decision-making, adaptation, human interaction, and governance. The framework organizes the functional requirements of HCDTs and is intended to inform future system design and comparison; its practical applicability and effectiveness require further validation. The review argues that HCDTs must extend beyond worker monitoring and productivity maximization: human data should inform industrial decisions that produce measurable improvements in safety, ergonomics, wellbeing, autonomy, accessibility, or skill development. Such systems should also uphold privacy, transparency, uncertainty awareness, explainability, and appropriate human authority. By linking technological capabilities to explicit worker outcomes, this synthesis enables researchers and engineers to assess the human-centeredness of HCDT implementations and supports the development of trustworthy systems for I5.0.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.