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EEG Sensor Based Classification for Assessing Psychological Stress
Mälardalen University, School of Innovation, Design and Engineering. (IS (Embedded Systems))ORCID iD: 0000-0002-1212-7637
Mälardalen University, School of Innovation, Design and Engineering.ORCID iD: 0000-0002-7305-7169
2013 (English)In: Studies in Health Technology and Informatics, Volume 189, 2013, IOS Press, 2013, 83-88 p.Conference paper, Published paper (Refereed)
Abstract [en]

Electroencephalogram (EEG) reflects the brain activity and is widely used in biomedical research. However, analysis of this signal is still a challenging issue. This paper presents a hybrid approach for assessing stress using the EEG signal. It applies Multivariate Multi-scale Entropy Analysis (MMSE) for the data level fusion. Case-based reasoning is used for the classification tasks. Our preliminary result indicates that EEG sensor based classification could be an efficient technique for evaluation of the psychological state of individuals. Thus, the system can be used for personal health monitoring in order to improve users health.

Place, publisher, year, edition, pages
IOS Press, 2013. 83-88 p.
Series
Studies in Health Technology and Informatics, ISSN 0926-9630 ; 188
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:mdh:diva-21351DOI: 10.3233/978-1-61499-268-4-83Scopus ID: 2-s2.0-84894233891ISBN: 9781614992677 (print)OAI: oai:DiVA.org:mdh-21351DiVA: diva2:649312
Conference
10th International Conference on Wearable Micro and Nano Technologies for Personalized Health, pHealth 2013; Tallinn; Estonia; 26 June 2013 through 28 June 2013
Available from: 2013-09-18 Created: 2013-09-11 Last updated: 2014-12-03Bibliographically approved

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CiteExportLink to record
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Cite
Citation style
  • apa
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  • vancouver
  • Other style
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Language
  • de-DE
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  • nn-NB
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Output format
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  • asciidoc
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