@inproceedings{5ff5fb9ef175465b98f4034284d7edd2,
title = "GenVibe: Exploration of Interactive Generation of Personal Vibrotactile Patterns",
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.",
keywords = "generative models, genetic algorithm, haptics, vibrotactile patterns",
author = "Erik Pescara and Florian Dreschner and Karola Marky and Kai Kunze and Michael Beigl",
note = "Publisher Copyright: {\textcopyright} 2020 ACM.; 2020 Augmented Humans International Conference, AHs 2020 ; Conference date: 16-03-2020 Through 17-03-2020",
year = "2020",
month = mar,
day = "16",
doi = "10.1145/3384657.3384794",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
booktitle = "Proceedings of the Augmented Humans International Conference, AHs 2020",
}