Ability-Based Methods for Personalized Keyboard Generation

TL;DR

This paper presents an ability-based method for creating personalized virtual keyboards by analyzing individual movement data, resulting in improved communication rates for users with different motor abilities.

Contribution

It introduces a novel approach that automatically characterizes user movement abilities to generate personalized keyboard layouts, enhancing communication efficiency.

Findings

Personalized keyboard increased communication rate to 52.0 bits/min.

Method effectively captures individual movement constraints and preferences.

Significant improvement over generic keyboard designs.

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.