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Authors: Julian Ramos ; Jin-Hyuk Hong and Anind K. Dey

Affiliation: Carnegie Mellon University, United States

Keyword(s): Stress Recognition, Physiological Responses, Physical Activity.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Biosignal Acquisition, Analysis and Processing ; Data Manipulation ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Processing of Multimodal Input ; Sensor Networks ; Soft Computing

Abstract: Despite the potential for stress and emotion recognition outside the lab environment, very little work has been reported that is feasible for use in the real world and much less for activities involving physical activity. In this work, we move a step forward towards a stress recognition system that works on a close to real world data set and shows a significant improvement over classification only systems. Our method uses clustering to separate the data into physical exertion levels and later performs stress classification over the discovered clusters. We validate our approach on a physiological stress dataset from 20 participants who performed 3 different activities of varying intensity under 3 different types of stimuli intended to cause stress. The results show an f-measure improvement of 130\% compared to using classification only.

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Paper citation in several formats:
Ramos, J.; Hong, J. and K. Dey, A. (2014). Stress Recognition - A Step Outside the Lab. In Proceedings of the International Conference on Physiological Computing Systems - PhyCS; ISBN 978-989-758-006-2; ISSN 2184-321X, SciTePress, pages 107-118. DOI: 10.5220/0004725701070118

@conference{phycs14,
author={Julian Ramos. and Jin{-}Hyuk Hong. and Anind {K. Dey}.},
title={Stress Recognition - A Step Outside the Lab},
booktitle={Proceedings of the International Conference on Physiological Computing Systems - PhyCS},
year={2014},
pages={107-118},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004725701070118},
isbn={978-989-758-006-2},
issn={2184-321X},
}

TY - CONF

JO - Proceedings of the International Conference on Physiological Computing Systems - PhyCS
TI - Stress Recognition - A Step Outside the Lab
SN - 978-989-758-006-2
IS - 2184-321X
AU - Ramos, J.
AU - Hong, J.
AU - K. Dey, A.
PY - 2014
SP - 107
EP - 118
DO - 10.5220/0004725701070118
PB - SciTePress

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