Buttons are the most commonly used input devices. So far the goal of the designers was to provide a passive button that can accept user input as easily as possible. Therefore, based on Fitts’ law, they maximize the size of the button and make the distance closer. This paper proposes Button++, a novel method to design smart buttons that actively judge user’s movement risk and selectively trigger input. Based on the latest model of moving target selection, Button++ tracks the user’s submovement just before the click and infers the expected error rate that can occur if the user repeatedly clicks with the same movement. This allows designers to make buttons that actively respond to the amount of risk in the user’s input movement.
|Title of host publication||CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems|
|Subtitle of host publication||Engage with CHI|
|Publisher||Association for Computing Machinery|
|ISBN (Electronic)||9781450356206, 9781450356213|
|Publication status||Published - 2018 Apr 20|
|Event||2018 CHI Conference on Human Factors in Computing Systems, CHI EA 2018 - Montreal, Canada|
Duration: 2018 Apr 21 → 2018 Apr 26
|Name||Conference on Human Factors in Computing Systems - Proceedings|
|Conference||2018 CHI Conference on Human Factors in Computing Systems, CHI EA 2018|
|Period||18/4/21 → 18/4/26|
Bibliographical noteFunding Information:
This research was supported the by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (NRF-2017R1C1B2002101).
© 2018 Copyright held by the owner/author(s).
All Science Journal Classification (ASJC) codes
- Human-Computer Interaction
- Computer Graphics and Computer-Aided Design