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https://hdl.handle.net/10216/15142| Author(s): | Jorge Teixeira Vasco Vinhas Luís Paulo Reis Eugénio Oliveira |
| Title: | Automatic emotion induction and assessment framework: enhancing user interfaces by interperting users multimodal biosignals |
| Issue Date: | 2009 |
| Abstract: | 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. |
| Description: | 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. |
| Subject: | Informática, Ciências da computação e da informação Informatics, Computer and information sciences |
| Scientific areas: | Ciências exactas e naturais::Ciências da computação e da informação Natural sciences::Computer and information sciences |
| URI: | https://hdl.handle.net/10216/15142 |
| Source: | ARTIFICIAL NEURAL NETWORK APPROACH FOR OBESITY-HYPERTENSION CLASSIFICATION |
| Document Type: | Artigo em Livro de Atas de Conferência Internacional |
| Rights: | openAccess |
| License: | https://creativecommons.org/licenses/by-nc/4.0/ |
| Appears in Collections: | FEUP - Artigo em Livro de Atas de Conferência Internacional |
This item is licensed under a Creative Commons License
