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

Joseph Onderi Orero

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Paper

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, 351-357, 2014 , Lisbon, Portugal

Author: Joseph Onderi Orero

Affiliation: Strathmore University, Kenya

Keyword(s): Affective Computing, Physiological Signals, Machine Learning,Prototypes, Typicality Degrees, Gameplay.

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 several formats:

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 (PhyCS 2014) - OASIS; ISBN 978-989-758-006-2; ISSN 2184-321X, SciTePress, pages 351-357. DOI: 10.5220/0004878403510357

@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 (PhyCS 2014) - OASIS},
year={2014},
pages={351-357},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004878403510357},
isbn={978-989-758-006-2},
issn={2184-321X},
}

TY - CONF

JO - Proceedings of the International Conference on Physiological Computing Systems (PhyCS 2014) - OASIS
TI - Typicality Degrees to Measure Relevance of the Physiological Signals - Assessing user’s Affective States
SN - 978-989-758-006-2
IS - 2184-321X
AU - Orero, J.
PY - 2014
SP - 351
EP - 357
DO - 10.5220/0004878403510357
PB - SciTePress