The helical axis is a common tool used in biomechanical modeling to parameterize the motion of rigid objects. It encodes an object's rotation around and translation along a unique axis. Visualizations of helical axes have helped to make kinematic data tangible. However, the analysis process often remains tedious, especially if complex motions are examined. We identify multiple key challenges: the absence of interactive tools for the computation and handling of helical axes, visual clutter in axis representations, and a lack of contextualization. We solve these issues by providing the first generalized framework for kinematic analysis with helical axes. Axis sets can be computed on-demand, interactively filtered, and explored in multiple coordinated views. We iteratively developed and evaluated the HAExplorer with active biomechanics researchers. Our results show that the techniques we introduce open up the possibility to analyze non-planar, compound, and interdependent motion data.
https://dl.acm.org/doi/abs/10.1145/3491102.3501841
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2022.acm.org/)