Descriptive Models of Emotion - Learning Useful Abstractions from Physiological Responses during Affective Interactions

Rui Henriques; Ana Paiva

Research.Publish.Connect.

*Please fill out at least one Field. *Value must be an number!

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Name:
Country:
Subject:

Advanced Search Affiliations Search

If you're looking for an exact phrase use quotation marks on text fields.

Proceedings

Proceedings Search *Please fill out at least one Field. *Value must be an number!

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

Papers

Papers Search *Please fill out at least one Field.

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

Authors

Authors Search *Please fill out at least one Field.

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

Advanced Search

Paper

Descriptive Models of Emotion - Learning Useful Abstractions from Physiological Responses during Affective Interactions

In Proceedings of the International Conference on Physiological Computing Systems - Volume 1: OASIS, 393-400, 2014 , Lisbon, Portugal

Authors: Rui Henriques and Ana Paiva

Affiliation: Instituto Superior Técnico and University of Lisbon, Portugal

Keyword(s): Descriptive Models, Mining Physiological Signals, Measuring Affective Interactions.

Abstract: Supervised recognition of emotions from physiological signals has been widely accomplished to measure affective interactions. Less attention is, however, placed upon learning descriptive models to characterize physiological responses. In this work we delve on why and how to learn discriminative, complete and usable descriptive models based on physiological signals from emotion-evocative stimuli. By satisfying these three properties, we guarantee that the target descriptors can be expressively adopted to understand the physiological behavior underlying multiple emotions. In particular, we explain why classification and unsupervised learning models do not address these properties, and point new directions on how to adapt existing learners to met them based on theoretical and empirical evidence.

CC BY-NC-ND 4.0

Guest: Register as new SciTePress user now for free.

SciTePress user: please login.

My Papers

You are not signed in, therefore limits apply to your IP address 3.133.139.164

In the current month:

Recent papers: 100 available of 100 total

2⁺ years older papers: 200 available of 200 total

Paper citation in several formats:

Henriques, R. and Paiva, A. (2014). Descriptive Models of Emotion - Learning Useful Abstractions from Physiological Responses during Affective Interactions. In Proceedings of the International Conference on Physiological Computing Systems (PhyCS 2014) - OASIS; ISBN 978-989-758-006-2; ISSN 2184-321X, SciTePress, pages 393-400. DOI: 10.5220/0004902703930400

@conference{oasis14,
author={Rui Henriques. and Ana Paiva.},
title={Descriptive Models of Emotion - Learning Useful Abstractions from Physiological Responses during Affective Interactions},
booktitle={Proceedings of the International Conference on Physiological Computing Systems (PhyCS 2014) - OASIS},
year={2014},
pages={393-400},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004902703930400},
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 - Descriptive Models of Emotion - Learning Useful Abstractions from Physiological Responses during Affective Interactions
SN - 978-989-758-006-2
IS - 2184-321X
AU - Henriques, R.
AU - Paiva, A.
PY - 2014
SP - 393
EP - 400
DO - 10.5220/0004902703930400
PB - SciTePress