AHFE Open AccessOptimization of Motion Capture Technology for a Human Digital Twin with Reduced Sensor Setups
Abstract
In recent years, ergonomic research has gained increasing prominence, highlighting the importance of analysing and improving workstation design to better support human workers and enhance task performance. Motion Capture technologies are widely used for ergonomic assessment and Human Digital Twin development; however, their practical deployment in industrial environments is often limited by complex setups, high costs, and lengthy calibration procedures. This study proposes a joint-level optimization methodology to reduce MoCap sensor requirements keeping motion reconstruction accuracy and the reliability of ergonomic evaluations. The approach leverages the posture prediction capabilities of the Digital Human Modelling IPS IMMA platform and validated through both controlled benchmark experiments and a real industrial use case.
Keywords: Human Digital Twin (HDT), Motion Capture (mocap), Digital Human Modelling (DHM)
DOI: 10.54941/ahfe1007698
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