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dc.contributor.authorMcDuff, Daniel Jonathan
dc.contributor.authorGontarek, Sarah
dc.contributor.authorPicard, Rosalind W.
dc.date.accessioned2016-07-20T15:16:44Z
dc.date.available2016-07-20T15:16:44Z
dc.date.issued2014-08
dc.identifier.isbn978-1-4244-7929-0
dc.identifier.otherINSPEC Accession Number: 14734443
dc.identifier.urihttp://hdl.handle.net/1721.1/103771
dc.description.abstractRemote detection of cognitive load has many powerful applications, such as measuring stress in the workplace. Cognitive tasks have an impact on breathing and heart rate variability (HRV). We show that changes in physiological parameters during cognitive stress can be captured remotely (at a distance of 3m) using a digital camera. A study (n=10) was conducted with participants at rest and under cognitive stress. A novel five band digital camera was used to capture videos of the face of the participant. Significantly higher normalized low frequency HRV components and breathing rates were measured in the stress condition when compared to the rest condition. Heart rates were not significantly different between the two conditions. We built a person-independent classifier to predict cognitive stress based on the remotely detected physiological parameters (heart rate, breathing rate and heart rate variability). The accuracy of the model was 85% (35% greater than chance).en_US
dc.description.sponsorshipMIT Media Lab Consortiumen_US
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/EMBC.2014.6944243en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceMIT web domainen_US
dc.titleRemote measurement of cognitive stress via heart rate variabilityen_US
dc.typeArticleen_US
dc.identifier.citationMcDuff, Daniel, Sarah Gontarek, and Rosalind Picard. "Remote measurement of cognitive stress via heart rate variability." in 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 26-30 Aug. 2014, Chicago, IL, IEEE, pp.2957-2960.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.departmentMassachusetts Institute of Technology. Media Laboratoryen_US
dc.contributor.mitauthorMcDuff, Daniel Jonathanen_US
dc.contributor.mitauthorGontarek, Sarahen_US
dc.contributor.mitauthorPicard, Rosalind W.en_US
dc.relation.journalProceedings of the 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Societyen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.identifier.pmid25570611
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsMcDuff, Daniel; Gontarek, Sarah; Picard, Rosalinden_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0002-5661-0022
mit.licenseOPEN_ACCESS_POLICYen_US


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