Quadmetric optimized thumb-to-finger interaction for force assisted one-handed text entry on mobile headsets
Lee, Lik Hang; Lam, Kit Yung; Li, Tong; Braud, Tristan; Su, Xiang; Hui, Pan (2019-09-30)
Lik Hang Lee, Kit Yung Lam, Tong Li, Tristan Braud, Xiang Su, and Pan Hui. 2019. Quadmetric Optimized Thumb-to-Finger Interaction for Force Assisted One-Handed Text Entry on Mobile Headsets. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 3, 3, Article 94 (September 2019), 27 pages. DOI:https://doi.org/10.1145/3351252
© 2019 Association for Computing Machinery. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous, Vol: 3:3, https://doi.org/10.1145/3351252.
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https://urn.fi/URN:NBN:fi-fe2020042923161
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Abstract
Augmented reality head-worn computers often feature small-sized touch interfaces that complicate interaction with content, provide insufficient space for comfortable text input, and can be awkward to use in social situations. This paper presents a novel one-handed thumb-to-finger text entry solution for augmented reality head-worn computers. We design a glove composed of 12 force-sensitive nodes featuring an ambiguous keyboard layout. We first explore the viability of force disambiguation to evaluate the force division within the force spectrum. We select a 3-level force division as it allows to considerably reduce the number of keys while featuring a high (83.9%) accuracy. Following this pilot study, we map the 26 English characters onto the 9 nodes located on the index, middle and ring fingers in a 3–3–3 configuration, and attribute the space, enter and backspace keys to the remaining three nodes. We consider text entry performance as a quadmetric optimization problem considering the following criteria: goodness of character pairs, layout similarity to the QWERTY keyboard, easiness of force interaction, and comfort level of thumb reach. The resulting layout strikes a balance between performance and usability. We finally evaluate the quadmetric optimized layout over 6 sessions with 12 participants. The participants achieve an average text entry rate of 6.47 WPM with 6.85% error rate in the final session, which is significantly faster than existing thumb-to-finger solutions. In addition, our one-handed text entry system enhances the user mobility compared to other state-of-the-art solutions by freeing one hand, while allowing the user to direct his visual attention to other activities.
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