Title
An Evaluation of Physiological Public Datasets for Emotion Recognition Systems
Date Issued
01 January 2021
Access level
open access
Resource Type
conference paper
Publisher(s)
Springer Science and Business Media Deutschland GmbH
Abstract
[Background] The performance of emotion recognition systems depends heavily on datasets used in their training, validation, or testing stages. [Aims] This research aims to evaluate the extent to which public available physiological datasets created for emotion recognition systems meet a set of reference requirements. [Method] Firstly, we analyze the applicability of some reference requirements proposed for stress datasets and adjust the corresponding evaluation criteria. Secondly, nine public physiological datasets were identified from a previous survey. [Results] None of the evaluated datasets satisfy all the reference requirements in order to be considered as a reference dataset for being used in the construction of reliable emotion recognition systems. [Conclusion] Although the evaluated datasets do not support the whole reference requirements, they provide a baseline for further development. Also, a greater effort is needed to establish specific reference requirements that can appropriately guide the creation of physiological datasets for emotion recognition systems.
Start page
90
End page
104
Volume
1410 CCIS
Language
English
OCDE Knowledge area
Sistemas de automatización, Sistemas de control
Subjects
Scopus EID
2-s2.0-85111098913
Source
Communications in Computer and Information Science
Resource of which it is part
Communications in Computer and Information Science
ISSN of the container
18650929
ISBN of the container
9783030762278
Conference
7th Annual International Conference on Information Management and Big Data, SIMBig 2020
Sponsor(s)
Acknowledgment. A. Mendoza, A. Cuno, N. Condori-Fernandez and W. Ramos acknowledge financial support from the “Proyecto Concytec - Banco Mundial, Mejo-ramiento y Ampliación de los Servicios del Sistema Nacional de Ciencia Tecnología e Innovación Tecnológica” 8682-PE, through its executing unit FONDECYT [Contract N◦ 014-2019-FONDECYT-BM-INC.INV]. Also, this work has been partially supported by Datos 4.0 (TIN2016-78011-C4-1-R) funded by MINECO-AEI/FEDER-UE.
Sources of information:
Directorio de Producción Científica
Scopus