Prediction of impulsive input on gamepad using force-sensitive resistor

Atsuya Munakata, Yuta Sugiura

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we propose a method to predict impulsive input on a gamepad. We use a force-sensitive resistor to observe pressure on the gamepad button, and prediction is achieved by simple filtering processes. To evaluate our method, we conducted a user study in which users were encouraged to make impulsive inputs. The results showed that the system predicted an ON event of the button 30.82 ms in advance on average and an OFF event 29.30 ms in advance. Prediction accuracy was 97.87% for predicting ON events and 81.74% for predicting OFF events.

Original languageEnglish
Title of host publicationTEI 2020 - Proceedings of the 14th International Conference on Tangible, Embedded, and Embodied Interaction
PublisherAssociation for Computing Machinery, Inc
Pages589-595
Number of pages7
ISBN (Electronic)9781450361071
DOIs
Publication statusPublished - 2020 Feb 6
Event14th International Conference on Tangible, Embedded, and Embodied Interaction, TEI 2020 - Sydney, Australia
Duration: 2020 Feb 92020 Feb 12

Publication series

NameTEI 2020 - Proceedings of the 14th International Conference on Tangible, Embedded, and Embodied Interaction

Conference

Conference14th International Conference on Tangible, Embedded, and Embodied Interaction, TEI 2020
CountryAustralia
CitySydney
Period20/2/920/2/12

Keywords

  • Force sensor
  • Gaming
  • Input device
  • Input prediction

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Human-Computer Interaction
  • Information Systems
  • Software

Fingerprint Dive into the research topics of 'Prediction of impulsive input on gamepad using force-sensitive resistor'. Together they form a unique fingerprint.

  • Cite this

    Munakata, A., & Sugiura, Y. (2020). Prediction of impulsive input on gamepad using force-sensitive resistor. In TEI 2020 - Proceedings of the 14th International Conference on Tangible, Embedded, and Embodied Interaction (pp. 589-595). (TEI 2020 - Proceedings of the 14th International Conference on Tangible, Embedded, and Embodied Interaction). Association for Computing Machinery, Inc. https://doi.org/10.1145/3374920.3374992