Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/52379
Registo completo
Campo DC | Valor | Idioma |
---|---|---|
dc.contributor.author | Gonçalves, Filipe Manuel | por |
dc.contributor.author | Carneiro, Davide Rua | por |
dc.contributor.author | Novais, Paulo | por |
dc.contributor.author | Pêgo, José M. | por |
dc.date.accessioned | 2018-03-14T15:04:04Z | - |
dc.date.available | 2018-03-14T15:04:04Z | - |
dc.date.issued | 2018 | - |
dc.identifier.citation | Gonçalves, F., Carneiro, D., Novais, P., & Pêgo, J. (2017, October). EUStress: A Human Behaviour Analysis System for Monitoring and Assessing Stress During Exams. In International Symposium on Intelligent and Distributed Computing (pp. 137-147). Springer, Cham | por |
dc.identifier.isbn | 978-3-319-66378-4 | - |
dc.identifier.issn | 1860-949X | por |
dc.identifier.uri | https://hdl.handle.net/1822/52379 | - |
dc.description.abstract | In today’s society, there is a compelling need for innovative approaches for the solution of many pressing problems, such as understanding the fluctuations in the performance of an individual when involved in complex and high-stake tasks. In these cases, individuals are under an increasing demand for performance, driving them to be under constant pressure, and consequently to present variations in their levels of stress. Human stress can be viewed as an agent, circumstance, situation, or variable that disturbs the normal functioning of an individual, that when not managed can bring mental problems, such as chronic stress or depression. In this paper, we propose a different approach for this problem. The EUStress application is a non-intrusive and non-invasive performance monitoring environment based on behavioural biometrics and real time analysis, used to quantify the level of stress of individuals during online exams. | por |
dc.description.sponsorship | FCT - Fuel Cell Technologies Program(NORTE-01-0247-FEDER-017832) | por |
dc.language.iso | eng | por |
dc.publisher | Springer Verlag | por |
dc.rights | openAccess | por |
dc.subject | Big data mining | por |
dc.subject | Decision making | por |
dc.subject | Human-computer interaction | por |
dc.subject | Mouse Dynamics | por |
dc.subject | Stress | por |
dc.title | EUStress: A human behaviour analysis system for monitoring and assessing stress during exams | por |
dc.type | conferencePaper | por |
dc.peerreviewed | yes | por |
dc.relation.publisherversion | https://link.springer.com/chapter/10.1007/978-3-319-66379-1_13#citeas | por |
oaire.citationStartPage | 137 | por |
oaire.citationEndPage | 147 | por |
oaire.citationVolume | 737 | por |
dc.date.updated | 2018-02-28T19:24:28Z | - |
dc.identifier.doi | 10.1007/978-3-319-66379-1_13 | por |
dc.identifier.eisbn | 978-3-319-66379-1 | - |
dc.subject.fos | Ciências Naturais::Ciências da Computação e da Informação | por |
dc.description.publicationversion | info:eu-repo/semantics/publishedVersion | por |
dc.subject.wos | Science & Technology | por |
sdum.export.identifier | 3088 | - |
sdum.journal | Studies in Computational Intelligence | por |
sdum.conferencePublication | INTELLIGENT DISTRIBUTED COMPUTING XI | por |
sdum.bookTitle | Intelligent Distributed Computing XI. IDC 2017 | por |
Aparece nas coleções: |