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The Performance and Preference of Different Fingers and Chords for Pointing, Dragging, and Object Transformation

Alix Goguey 1 Mathieu Nancel 2 Géry Casiez 3, 1 Daniel Vogel 2
1 MJOLNIR - Computing tools to empower users
Inria Lille - Nord Europe, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
Abstract : The development of robust methods to identify which finger is causing each touch point, called “finger identification,” will open up a new input space where interaction designers can associate system actions to different fingers. However, relatively little is known about the performance of specific fingers as single touch points or when used together in a “chord.” We present empirical results for accuracy, throughput, and subjective preference gathered in five experiments with 48 participants exploring all 10 fingers and 7 two-finger chords. Based on these results, we develop design guidelines for reasonable target sizes for specific fingers and two-finger chords, and a relative ranking of the suitability of fingers and two-finger chords for common multi-touch tasks. Our work contributes new knowledge regarding specific finger and chord performance and can inform the design of future interaction techniques and interfaces utilizing finger identification.
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Alix Goguey, Mathieu Nancel, Géry Casiez, Daniel Vogel. The Performance and Preference of Different Fingers and Chords for Pointing, Dragging, and Object Transformation. In Proceedings of CHI'16, the 34th Conference on Human Factors in Computing Systems, May 2016, San Jose, United States. pp.4250-4261, ⟨10.1145/2858036.2858194⟩. ⟨hal-01267607⟩

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