Remote physiological and GPS data processing in evaluation of physical activities.
The monitoring of data from global positioning system (GPS) receivers and remote sensors of physiological and environmental data allow forming an information database for observed data processing. In this paper, we propose the use of such a database for the analysis of physical activities during cyc...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 52; no. 4; pp. 301 - 309 |
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| Autores principales: | , , , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Springer Nature
Apr2014
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104048246&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104048246 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Apr2014 vid: 52 iid: 4 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104048246 NLM24366843 2012516388 10.1007/s11517-013-1134-6 NLM24366843 104048246 ppf: 301 ppct: 8 formats: fmt: @attributes: type: P tig: atl: Remote physiological and GPS data processing in evaluation of physical activities. aug: au: Procházka, Ales Vaseghi, Saeed Yadollahi, Mohammadreza Tupa, Ondej Mares, Jan Vysata, Oldich Procházka, Aleš Tupa, Ondřej Mareš, Jan Vyšata, Oldřich affil: Department of Computing and Control Engineering, Institute of Chemical Technology in Prague, 166 28, Prague, Czech Republic sug: subj: Geographic Information Systems Signal Processing, Computer Assisted Telemetry Methods Algorithms Cycling Physiology Geographic Factors Heart Rate Physiology Human Regression ab: The monitoring of data from global positioning system (GPS) receivers and remote sensors of physiological and environmental data allow forming an information database for observed data processing. In this paper, we propose the use of such a database for the analysis of physical activities during cycling. The main idea of the proposed algorithm is to use cross-correlations between the heart rate and the altitude gradient to evaluate the delay between these variables and to study its time evolution. The data acquired during 22 identical cycling routes, each about 130 km long, include more than 6,700 segments of length 60 s recorded with varying sampling periods. General statistical and digital signal processing methods used include mathematical tools to reject gross errors, resampling using selected interpolation methods, digital filtering of noise signal components, and estimating cross-correlations between the position data and the physiological signals. The results of a regression between GPS and physiological data include the estimate of the time delay between the heart rate change and gradient altitude of about 7.5 s and its decrease during each training route. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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