Ability-based methods for personalized keyboard generation
OA Version
Citation
C.L. Mitchell, G.J. Cler, S.K. Fager, P. Contessa, S.H. Roy, G. De Luca, J.C. Kline, J.M. Vojtech. 2022. "Ability-Based Methods for Personalized Keyboard Generation." Multimodal Technologies and Interaction, Volume 6, Issue 8, pp.67-. https://doi.org/10.3390/mti6080067
Abstract
This study introduces an ability-based method for personalized keyboard generation, wherein an individual's own movement and human-computer interaction data are used to automatically compute a personalized virtual keyboard layout. Our approach integrates a multidirectional point-select task to characterize cursor control over time, distance, and direction. The characterization is automatically employed to develop a computationally efficient keyboard layout that prioritizes each user's movement abilities through capturing directional constraints and preferences. We evaluated our approach in a study involving 16 participants using inertial sensing and facial electromyography as an access method, resulting in significantly increased communication rates using the personalized keyboard (52.0 bits/min) when compared to a generically optimized keyboard (47.9 bits/min). Our results demonstrate the ability to effectively characterize an individual's movement abilities to design a personalized keyboard for improved communication. This work underscores the importance of integrating a user's motor abilities when designing virtual interfaces.
Description
License
Copyright: Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).