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The term human digital twin has recently been applied in many domains, including medical and manufacturing. This term extends the digital twin concept, which has been illustrated to provide enhanced system performance as it combines system models and analyses with real-time measurements for an individual system to improve system maintenance. Human digital twins have the potential to change the practice of human system integration as these systems employ real-time sensing and feedback to tightly couple measurements of human performance, behavior, and environmental influences throughout a product’s life cycle to human models to improve system design and performance. However, as this concept is relatively new, the literature lacks inclusive and precise definitions of this concept. The current research reviews the literature on human digital twins to provide a generalized structure of these systems, provide definitions of a human digital twin and human digital twin system, and review the potential applications of these systems within product design, development, and sustainment. This review of the existing literature suggests that components of human models sufficient to provide robust human digital twins are likely to be derived across multiple fields of study. Thus, development of these systems would benefit an open multi-disciplinary research effort.


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Human-Intelligent Systems Integration