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Physiological and GPS data fusion

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dc.title Physiological and GPS data fusion en
dc.contributor.author Charvátová, Hana
dc.contributor.author Procházka, Aleš
dc.contributor.author Vaseghi, Saeed V.
dc.contributor.author Vyšata, Oldřich
dc.contributor.author Janáčová, Dagmar
dc.contributor.author Líška, Ondrej
dc.relation.ispartof 2015 International Workshop on Computational Intelligence for Multimedia Understanding, IWCIM 2015
dc.identifier.isbn 978-1-4673-8457-5
dc.date.issued 2015
dc.event.title 2015 International Workshop on Computational Intelligence for Multimedia Understanding, IWCIM 2015
dc.event.location Prague
utb.event.state-en Czech Republic
utb.event.state-cs Česká republika
dc.event.sdate 2015-10-29
dc.event.edate 2015-10-30
dc.type conferenceObject
dc.language.iso en
dc.publisher Institute of Electrical and Electronics Engineers Inc.
dc.identifier.doi 10.1109/IWCIM.2015.7347065
dc.relation.uri http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7347065
dc.subject Data fusion en
dc.subject digital filters en
dc.subject digital signal processing en
dc.subject GPS data processing en
dc.subject interpolation en
dc.subject regression en
dc.description.abstract The paper deals with fusion of physiological and GPS data acquired during cycling and their analysis using general methods of multichannel signal processing. Experimental data were acquired during 17 identical cycling routes each about 12 km long including more then 1100 segments of the length 60 s recorded with the varying sampling period. The proposed algorithm includes their initial analysis, de-nosing using selected digital filters, interpolation and resampling in the first stage followed by evaluation of the cross-correlation between the heart rate and the altitude gradient of positioning data recorded by the GPS system. Results obtained present (i) relation between the heart rate and the slope with the positive regression coefficient 6.04 and (ii) the heart rate and speed with the negative regression coefficient-1.67 over all segments analyzed. © 2015 IEEE. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1006311
utb.identifier.obdid 43873799
utb.identifier.scopus 2-s2.0-84962892127
utb.identifier.wok 000380431200005
utb.source d-scopus
dc.date.accessioned 2016-06-22T12:14:44Z
dc.date.available 2016-06-22T12:14:44Z
utb.contributor.internalauthor Charvátová, Hana
utb.contributor.internalauthor Janáčová, Dagmar
utb.fulltext.affiliation H. Charvátová 1, A. Procházka 2,4, S. Vaseghi 2, O. Vyšata 3, D. Janáčová 1, O. Líška 5 1 Tomas Bata University in Zlín, Faculty of Applied Informatics, CZ 2 Czech Institute of Informatics, Robotics and Cybernetics, Czech Technical University, Prague, CZ 3 Charles University, Department of Neurology in Hradec Králové, CZ 4 University of Chemistry and Technology, Prague, Dept of Computing and Control Eng., Prague, CZ 5 Technical University of Kosice, Mechanical Engineering Faculty, SK
utb.fulltext.dates -
utb.fulltext.faculty Faculty of Applied Informatics
utb.fulltext.faculty Faculty of Applied Informatics
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