Adrien Chaffangeon Caillet
Laboratoire d'Informatique de Grenoble, Grenoble, France
In the active field of hand microgestures, microgesture descriptions are typically expressed informally and are accompanied by images, leading to ambiguities and contradictions. An important step in moving the field forward is a rigorous basis for precisely describing, comparing, and analyzing microgestures. Towards this goal, we propose µGlyph, a hybrid notation based on a vocabulary of events inspired by finger biomechanics. First, we investigate the expressiveness of µGlyph by building a database of 118 microgestures extracted from the literature. Second, we experimentally explore the usability of µGlyph. Participants correctly read and wrote µGlyph descriptions 90% of the time, as compared to 46% for conventional descriptions. Third we present tools that promote µGlyph usage, including a visual editor with LaTeX export. We finally describe how µGlyph can guide research on designing, developing, and evaluating microgesture interaction. Results demonstrate the strong potential of µGlyph to establish a common ground for microgesture research.
https://doi.org/10.1145/3544548.3580693
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2023.acm.org/)