A New Approach to Emotion Assessment Based on Biometric Data

Several knowledge areas such as psychology, medicine and computer science have been devoting serious efforts regarding emotional state definition, identification and assessment. This project consists in an automatic emotion assessment tool based on biometric data acquisition supported by low-budget...

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Vydáno v:Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03 Ročník 3; s. 505 - 511
Hlavní autoři: Teixeira, Jorge, Vinhas, Vasco, Oliveira, Eugénio, Reis, Luís Paulo
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: Washington, DC, USA IEEE Computer Society 09.12.2008
IEEE
Edice:ACM Conferences
Témata:
Applied computing > Life and medical sciences
Applied computing > Life and medical sciences > Computational biology
Applied computing > Life and medical sciences > Genetics
Applied computing > Life and medical sciences > Systems biology
Artificial intelligence
Bioinformatics
Computer science
Computing methodologies > Machine learning > Learning paradigms > Supervised learning > Supervised learning by classification
Computing methodologies > Machine learning > Machine learning approaches > Classification and regression trees
Data Analysis and Processing
Electroencephalograph
Electroencephalography
Emotion Assessment
Hardware
Humans
Intelligent agent
Medical Signal Acquisition
Multimedia systems
Pervasive computing
Ubiquitous computing
Medical Signal Acquisition
Electroencephalograph
Artificial Intelligence
Data Analysis and Processing
Emotion Assessment
ISBN:9780769534961, 0769534961
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Popis
Shrnutí:Several knowledge areas such as psychology, medicine and computer science have been devoting serious efforts regarding emotional state definition, identification and assessment. This project consists in an automatic emotion assessment tool based on biometric data acquisition supported by low-budget biometric devices as a electroencephalograph and a galvanic skin response. The classification is grounded on data analysis and processing of standard emotional induction methods. The numerous conducted experimental sessions,alongside with the developed support tools, allowed the extraction of conclusions such as the capability of effectively performing automatic classification of the subject’s predominant emotional state. The developed tool's success rate, validated against self assessment interviews, was approximately 75%. It was also experimentally concluded that female subjects are emotionally more active and easily induced than males.
ISBN:9780769534961
0769534961
DOI:10.1109/WIIAT.2008.253