Publication:
Data-driven vibrotactile rendering of digital buttons on touchscreens

Placeholder

School / College / Institute

Organizational Unit

Program

KU Authors

Co-Authors

Publication Date

Language

Embargo Status

Journal Title

Journal ISSN

Volume Title

Alternative Title

Abstract

Interaction with physical buttons is an essential part of our daily routine. We use buttons daily to turn lights on, to call an elevator, to ring a doorbell, or even to turn on our mobile devices. Buttons have distinct response characteristics and are easily activated by touch. However, there is limited tactile feedback available for their digital counterparts displayed on touchscreens. Although mobile phones incorporate low-cost vibration motors to enhance touch-based interactions, it is not possible to generate complex tactile effects on touchscreens. It is also difficult to relate the limited vibrotactile feedback generated by these motors to different types of physical buttons. In this study, we focus on creating vibrotactile feedback on a touchscreen that simulates the feeling of physical buttons using piezo actuators attached to it. We first recorded and analyzed the force, acceleration, and voltage data from twelve participants interacting with three different physical buttons: latch, toggle, and push buttons. Then, a button-specific vibrotactile stimulus was generated for each button based on the recorded data. Finally, we conducted a three-alternative forced choice (3AFC) experiment with twenty participants to explore whether the resultant stimulus is distinct and realistic. In our experiment, participants were able to match the three digital buttons with their physical counterparts with a success rate of 83%. In addition, we harvested seven adjective pairs from the participants expressing their perceptual feeling of pressing the physical buttons. All twenty participants rated the degree of their subjective feelings associated with each adjective for all the physical and digital buttons investigated in this study. Our statistical analysis showed that there exist at least three adjective pairs for which participants have rated two out of three digital buttons similar to their physical counterparts.

Source

Publisher

Academic Press Ltd- Elsevier Science Ltd

Subject

Computer science, Cbernetics, Human engineering, Psychology

Citation

Has Part

Source

International Journal of Human-Computer Studies

Book Series Title

Edition

DOI

10.1016/j.ijhcs.2019.09.005

item.page.datauri

Link

Rights

Copyrights Note

Endorsement

Review

Supplemented By

Referenced By

1

Views

0

Downloads

View PlumX Details