A physical load metric development for assessment of mixed reality in aircraft inspection tasks

Advancements in digital data-driven aircraft sustainment for mission-critical systems imposes diverse digitisation demands on humans. This poses a challenge of seamless integration of the data-enabled mixed reality systems consistent with biological responses of a human in the loop. In this paper, we 1) develop a human physical load measuring system; 2) assess feasibility of measuring human physical load in aircraft maintenance task execution; and 3) assess captured objective and subjective physical load data for suitability to assess maintenance task training efficiency. Such a system will enable assessment of mixed reality in its application in Defence aircraft maintenance environments, to identify limitations of the technology, gaps in the systems, and opportunities for further development. In this regard, a non-obtrusive methodology was developed to collect real-time human skeletal movement data using computer vision and deep learning to assess human physical loads during one of the aircraft inspection tasks.