Typicality Degrees to Measure Relevance of the Physiological Signals - Assessing user’s Affective States

Joseph Onderi Orero

2014

Abstract

Physiological measures have a key advantage as they can provide an insight into human feelings that the subjects may not even be consciously aware of. However, modeling user affective states through pysiology still remains with critical questions especially on the relevant physiological measures for real-life emotionally intelligent applications. In this study, we propose the use of typicality degrees defined according to cognitive science and psychology principles to measure the relevance of the physiological features in characterizing user affective states. Thanks to the typicality degrees, we found consistent physiological characteristics for modeling user affective states.

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Paper Citation


in Harvard Style

Orero J. (2014). Typicality Degrees to Measure Relevance of the Physiological Signals - Assessing user’s Affective States . In Proceedings of the International Conference on Physiological Computing Systems - Volume 1: OASIS, (PhyCS 2014) ISBN 978-989-758-006-2, pages 351-357. DOI: 10.5220/0004878403510357


in Bibtex Style

@conference{oasis14,
author={Joseph Onderi Orero},
title={Typicality Degrees to Measure Relevance of the Physiological Signals - Assessing user’s Affective States},
booktitle={Proceedings of the International Conference on Physiological Computing Systems - Volume 1: OASIS, (PhyCS 2014)},
year={2014},
pages={351-357},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004878403510357},
isbn={978-989-758-006-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Physiological Computing Systems - Volume 1: OASIS, (PhyCS 2014)
TI - Typicality Degrees to Measure Relevance of the Physiological Signals - Assessing user’s Affective States
SN - 978-989-758-006-2
AU - Orero J.
PY - 2014
SP - 351
EP - 357
DO - 10.5220/0004878403510357