Abstract
Real-time optimization-based posture prediction has fostered the development of zone differentiation, whereby performance-measure values resulting from a predicted posture are evaluated and displayed for large volumes of target points surrounding an avatar. To date, this tool was limited with respect to computational speed and practical applications. This paper presents a series of improvements and new features, including new algorithms for sphere filling and collision avoidance, significant increases to computational speed, incorporation of whole-body posture prediction, new methods for visualizing results, and multi-dimensional zone differentiation, which is the ability to automatically calculate multiple zones for various sets of problem parameters. These new tools collectively advance human systems integration. They are successfully applied to three example problems and demonstrate the ability to direct product design virtually, based on human performance.
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Marler, T., Beck, S., Verma, U., Johnson, R., Roemig, V., Dariush, B. (2014). A Digital Human Model for Performance-Based Design. In: Duffy, V.G. (eds) Digital Human Modeling. Applications in Health, Safety, Ergonomics and Risk Management. DHM 2014. Lecture Notes in Computer Science, vol 8529. Springer, Cham. https://doi.org/10.1007/978-3-319-07725-3_13
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DOI: https://doi.org/10.1007/978-3-319-07725-3_13
Publisher Name: Springer, Cham
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