GenVibe: Exploration of Interactive Generation of Personal Vibrotactile Patterns

Erik Pescara, Florian Dreschner, Karola Marky, Kai Kunze, Michael Beigl

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

Abstract

Research about vibrotactile patterns is traditionally conducted with patterns handcrafted by experts which are then subsequently evaluated in general user studies. The current empirical approach to designing vibrotactile patterns mostly utilizes expert decisions and is notably not adapted to individual differences in the perception of vibration. This work describes GenVibe: a novel approach to designing vibrotactile patterns by examining the automatic generation of personal patterns. GenVibe adjusts patterns to the perception of an individual through the utilization of interactive generative models. An algorithm is described and tested with a dummy smartphone made from off-the-shelf electronic components. Afterward, a user study with 11 participants evaluates the outcome of GenVibe. Results show a significant increase in accuracy from 73.6% to 84.0% and a higher confidence ratings by the users.

Original languageEnglish
Title of host publicationProceedings of the Augmented Humans International Conference, AHs 2020
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450376037
DOIs
Publication statusPublished - 2020 Mar 16
Event2020 Augmented Humans International Conference, AHs 2020 - Kaiserslautern, Germany
Duration: 2020 Mar 162020 Mar 17

Publication series

NameACM International Conference Proceeding Series

Conference

Conference2020 Augmented Humans International Conference, AHs 2020
CountryGermany
CityKaiserslautern
Period20/3/1620/3/17

Keywords

  • generative models
  • genetic algorithm
  • haptics
  • vibrotactile patterns

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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