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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 |