Document type
Journal articles
Document subtype
Full paper
Title
metaFERA: a meta-framework for creating emotion recognition frameworks for physiological signals
Participants in the publication
João Oliveira (Author)
FACULDADE DE CIÊNCIAS DA UNIVERSIDADE DE LISBOA
Soraia M. Alarcão (Author)
FACULDADE DE CIÊNCIAS DA UNIVERSIDADE DE LISBOA
Dep. Informática
Teresa Chambel (Author)
FACULDADE DE CIÊNCIAS DA UNIVERSIDADE DE LISBOA
Dep. Informática
LASIGE
Manuel J. Fonseca (Author)
FACULDADE DE CIÊNCIAS DA UNIVERSIDADE DE LISBOA
Dep. Informática
LASIGE
Summary
Recognizing emotions from physiological signals has proven to be important in various scenarios. To assist in developing emotion recognizers, software frameworks and toolboxes have emerged, offering ready-to-use components. However,these have limitations regarding the type of physiological signals supported, the recognition steps covered, or the acquisition of multiple physiological signals. This paper presents metaFERA, an architectural meta-framework for creating software frameworks for end-to-end emotion recognition from physiological signals. The modularity and flexibility of the meta-framework and the resulting frameworks allow the fast prototyping of emotion recognition systems and experiments to test and validate new algorithms. To that end, metaFERA offers: (i) a set of pre-configured blocks to which we can add behavior to create framework components; (ii) an easy way to add behavior to the pre-configured blocks; (iii) a channel-based communication mechanism that transparently and efficiently supports the exchange of information between components; (iv) a simple and easy way to use and link components from a resulting framework to create applications. Additionally, we provide a set of Web services, already configured, to make the resulting recognition systems available as a service. To validate metaFERA, we created a framework for Electrodermal Activity, an emotion recognizer to identify high/low arousal using the aforementioned framework, and a layer to offer the recognizer as a service.
Date of Publication
2023-06-26
Institution
FACULDADE DE CIÊNCIAS DA UNIVERSIDADE DE LISBOA
Where published
Multimedia Tools and Applications
Publication Identifiers
ISSN - 1380-7501
Publisher
Springer Science and Business Media LLC
Document Identifiers
DOI -
https://doi.org/10.1007/s11042-023-15249-5
URL -
http://dx.doi.org/10.1007/s11042-023-15249-5
Rankings
SCOPUS Q1 (2022) - 0.145 - Media Technology
SCIMAGO Q1 (2022) - 0.72 - Media Technology