Automatic Stress Detection Using Non-Eeg Biological Signal

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but.event.date25.04.2019cs
but.event.titleStudent EEICT 2019cs
dc.contributor.authorMalina, Ondřej
dc.date.accessioned2020-04-16T07:19:26Z
dc.date.available2020-04-16T07:19:26Z
dc.date.issued2019cs
dc.description.abstractThis work deals with the issue of stress detection using non-EEG biosignals. The main goal of this work is to create a functional program in MATLAB programming language that would allow detection and classification of stress, from easily readable data acquired on commercially available devices. So that esults obtained by this algorithm can be used for predicting and preventing stress during daily routine activities.en
dc.formattextcs
dc.format.extent38-41cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationProceedings of the 25st Conference STUDENT EEICT 2019. s. 38-41. ISBN 978-80-214-5735-5cs
dc.identifier.isbn978-80-214-5735-5
dc.identifier.urihttp://hdl.handle.net/11012/186612
dc.language.isocscs
dc.publisherVysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.relation.ispartofProceedings of the 25st Conference STUDENT EEICT 2019en
dc.relation.urihttp://www.feec.vutbr.cz/EEICT/cs
dc.rights© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.rights.accessopenAccessen
dc.subjectstress classificationen
dc.subjectnon-EEG biosignalsen
dc.subjectMATLABen
dc.subjectc-meansen
dc.subjectPhysioNeten
dc.titleAutomatic Stress Detection Using Non-Eeg Biological Signalen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.departmentFakulta elektrotechniky a komunikačních technologiícs
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