Ability-Based Methods for Personalized Keyboard Generation
This work addresses the problem of inefficient communication interfaces for individuals with motor impairments, representing an incremental improvement over generic optimization methods.
The study tackled the problem of improving communication rates for users with motor impairments by generating personalized virtual keyboard layouts based on individual movement abilities, resulting in a significant increase from 47.9 to 52.0 bits/min.
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.