Emotion Recognition through Keystroke Dynamics on Touchscreen Keyboards

Matthias Trojahn, Florian Arndt, Markus Weinmann, Frank Ortmeier

2013

Abstract

Automatic emotion recognition through computers offers a lot of advantages, as the interaction between human and computers can be improved. For example, it is possible to be responsive to anger or frustration of customers automatically while working with a webpage. Mouse cursor movements and keystroke dynamics were already used and examined for such a recognition on conventional keyboards. The aim of this work is to investigate keystroke dynamics on touchscreen keyboards which gets a cumulative relevance through the increasingly further circulation of smartphones and tablets. Furthermore, it is possible to record additional information like pressure and size of keystrokes. This could increase the recognition rate for emotions. In order to record the keystroke dynamics, an application and keyboard layout for Android OS were developed. In addition, hypotheses were established on the basis of Yerkes-Dodson-Law and Flow theory and besides, a study with 152 test persons for the data collection was implemented. Subsequently, a data evaluation with the SPSS software was accomplished. Most of the hypotheses were confirmed and the results of the study show that emotions can be explained by the keystroke dynamics and recognized in this way.

Paper Citation

in Harvard Style

Trojahn M., Arndt F., Weinmann M. and Ortmeier F. (2013). Emotion Recognition through Keystroke Dynamics on Touchscreen Keyboards . In Proceedings of the 15th International Conference on Enterprise Information Systems - Volume 3: ICEIS, ISBN 978-989-8565-61-7, pages 31-37. DOI: 10.5220/0004415500310037

in Bibtex Style

@conference{iceis13,
author={Matthias Trojahn and Florian Arndt and Markus Weinmann and Frank Ortmeier},
title={Emotion Recognition through Keystroke Dynamics on Touchscreen Keyboards},
booktitle={Proceedings of the 15th International Conference on Enterprise Information Systems - Volume 3: ICEIS,},
year={2013},
pages={31-37},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004415500310037},
isbn={978-989-8565-61-7},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 15th International Conference on Enterprise Information Systems - Volume 3: ICEIS,
TI - Emotion Recognition through Keystroke Dynamics on Touchscreen Keyboards
SN - 978-989-8565-61-7
AU - Trojahn M.
AU - Arndt F.
AU - Weinmann M.
AU - Ortmeier F.
PY - 2013
SP - 31
EP - 37
DO - 10.5220/0004415500310037