FingerText, CHI 2021

DoYoung Lee, Jiwan Kim, and Ian Oakley. 2021. FingerText: Exploring and Optimizing Performance for Wearable, Mobile and One-Handed Typing. Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, New York, NY, USA, Article 283, 1–15. DOI:https://doi.org/10.1145/3411764.3445106

Abstract

Typing on wearables while situationally impaired, such as while walking, is challenging. However, while HCI research on wearable typing is diverse, existing work focuses on stationary scenarios and fine-grained input that will likely perform poorly when users are on-the-go. To address this issue we explore single-handed wearable typing using intra-hand touches between the thumb and fingers, a modality we argue will be robust to the physical disturbances inherent to input while mobile. We first examine the impact of walking on performance of these touches, noting no significant differences in accuracy or speed, then feed our study data into a multi-objective optimization process in order to design keyboard layouts (for both five and ten keys) capable of supporting rapid, accurate, comfortable, and unambiguous typing. A final study tests these layouts against QWERTY baselines and reports performance improvements of up to 10.45% WPM and 39.44% WER when users type while walking.