Latent gaze information in highly dynamic decision-tasks. (arXiv:2202.04072v1 [cs.HC])

Digitization is penetrating more and more areas of life. Tasks are
increasingly being completed digitally, and are therefore not only fulfilled
faster, more efficiently but also more purposefully and successfully. The rapid
developments in the field of artificial intelligence in recent years have
played a major role in this, as they brought up many helpful approaches to
build on. At the same time, the eyes, their movements, and the meaning of these
movements are being progressively researched. The combination of these
developments has led to exciting approaches. In this dissertation, I present
some of these approaches which I worked on during my Ph.D.

First, I provide insight into the development of models that use artificial
intelligence to connect eye movements with visual expertise. This is
demonstrated for two domains or rather groups of people: athletes in
decision-making actions and surgeons in arthroscopic procedures. The resulting
models can be considered as digital diagnostic models for automatic expertise
recognition. Furthermore, I show approaches that investigate the
transferability of eye movement patterns to different expertise domains and
subsequently, important aspects of techniques for generalization. Finally, I
address the temporal detection of confusion based on eye movement data. The
results suggest the use of the resulting model as a clock signal for possible
digital assistance options in the training of young professionals. An
interesting aspect of my research is that I was able to draw on very valuable
data from DFB youth elite athletes as well as on long-standing experts in
arthroscopy. In particular, the work with the DFB data attracted the interest
of radio and print media, namely DeutschlandFunk Nova and SWR DasDing. All
resulting articles presented here have been published in internationally
renowned journals or at conferences.

Source: https://arxiv.org/abs/2202.04072

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