Automatic emotion induction and assessment framework: enhancing user interfaces by interperting users multimodal biosignals

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2009

Autores

Jorge Teixeira (Autor) FEUP; Vasco Vinhas (Autor) Outra; Luís Paulo Reis (Autor) FEUP; Eugénio Oliveira (Autor) FEUP

Ata de Conferência Internacional

Título: ARTIFICIAL NEURAL NETWORK APPROACH FOR OBESITY-HYPERTENSION CLASSIFICATION

Páginas: 487-490

BIOSTEC 2009 - Second International Joint Conference on Biomedical Engineering Systems and Technologies

Vila Nova de Gaia, Portugal, 14 a 17 de Janeiro de 2009

Indexação

ISI Web of Knowledge - 1 Citação

Scopus - 4 Citações

Classificação Científica

FOS: Ciências exactas e naturais > Ciências da computação e da informação

CORDIS: Ciências Físicas > Ciência de computadores > Informática

Outras Informações

ID Authenticus: P-003-PA5

Resumo (PT): Emotion's definition, identification, systematic induction and efficient and reliable classification have been themes to which several complementary knowledge areas such as psychology, medicine and computer science have been dedicating serious investments. This project consists in developing an automatic tool for emotion assessment based on a dynamic biometric data acquisition set as galvanic skin response and electroencephalography arc practical examples. The output of standard emotional induction methods is the support for classification based on data analysis and processing. The conducted experimental sessions, alongside with the developed support tools, allowed the extraction on conclusions such as the capability of effectively performing automatic classification of the subject's predominant emotional state. Self assessment interviews validated the developed tool's success rate of approximately 75%. It was also experimentally strongly suggested that female subjects are emotionally more active and easily induced than mates.

Abstract (EN): Emotion's definition, identification, systematic induction and efficient and reliable classification have been themes to which several complementary knowledge areas such as psychology, medicine and computer science have been dedicating serious investments. This project consists in developing an automatic tool for emotion assessment based on a dynamic biometric data acquisition set as galvanic skin response and electroencephalography arc practical examples. The output of standard emotional induction methods is the support for classification based on data analysis and processing. The conducted experimental sessions, alongside with the developed support tools, allowed the extraction on conclusions such as the capability of effectively performing automatic classification of the subject's predominant emotional state. Self assessment interviews validated the developed tool's success rate of approximately 75%. It was also experimentally strongly suggested that female subjects are emotionally more active and easily induced than mates.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 4