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Arousal and Valence Recognition of Affective Sounds Based on Electrodermal Activity

Greco, Alberto and Valenza, Gaetano and Citi, Luca and Scilingo, Enzo Pasquale (2017) 'Arousal and Valence Recognition of Affective Sounds Based on Electrodermal Activity.' IEEE Sensors Journal, 17 (3). 716 - 725. ISSN 1530-437X

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Abstract

Physiological sensors and interfaces for mental healthcare are becoming of great interest in research and commercial fields. Specifically, biomedical sensors and related ad hoc signal processing methods can be profitably used for supporting objective, psychological assessments. However, a simple system able to automatically classify the emotional state of a healthy subject is still missing. To overcome this important limitation, we here propose the use of convex optimization-based electrodermal activity (EDA) framework and clustering algorithms to automatically discern arousal and valence levels induced by affective sound stimuli. EDA recordings were gathered from 25 healthy volunteers, using only one EDA sensor to be placed on fingers. Standardized stimuli were chosen from the International Affective Digitized Sound System database, and grouped into four different levels of arousal (i.e., the levels of emotional intensity) and two levels of valence (i.e., how unpleasant/pleasant a sound can be perceived). Experimental results demonstrated that our system is able to achieve a recognition accuracy of 77.33% on the arousal dimension, and 84% on the valence dimension.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > RA Public aspects of medicine > RA790 Mental Health
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Jim Jamieson
Date Deposited: 31 Mar 2017 09:10
Last Modified: 04 Jul 2018 14:15
URI: http://repository.essex.ac.uk/id/eprint/19414

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