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Statements

Subject Item
n2:RIV%2F00216208%3A11150%2F14%3A10193365%21RIV15-MSM-11150___
rdf:type
n9:Vysledek skos:Concept
rdfs:seeAlso
http://link.springer.com/article/10.1007%2Fs11517-013-1134-6
dcterms:description
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. 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.
dcterms:title
Remote physiological nad GPS data processing in evaluation of physical activities Remote physiological nad GPS data processing in evaluation of physical activities
skos:prefLabel
Remote physiological nad GPS data processing in evaluation of physical activities Remote physiological nad GPS data processing in evaluation of physical activities
skos:notation
RIV/00216208:11150/14:10193365!RIV15-MSM-11150___
n4:aktivita
n10:I
n4:aktivity
I
n4:cisloPeriodika
4
n4:dodaniDat
n12:2015
n4:domaciTvurceVysledku
n17:1501208
n4:druhVysledku
n6:J
n4:duvernostUdaju
n15:S
n4:entitaPredkladatele
n7:predkladatel
n4:idSjednocenehoVysledku
42147
n4:idVysledku
RIV/00216208:11150/14:10193365
n4:jazykVysledku
n18:eng
n4:klicovaSlova
physiological signal processing; correlation analysis; digital filters; interpolation; signal resampling; remote data acquisition; GPS data processing; digital signal analysis
n4:klicoveSlovo
n5:remote%20data%20acquisition n5:physiological%20signal%20processing n5:signal%20resampling n5:digital%20filters n5:digital%20signal%20analysis n5:correlation%20analysis n5:GPS%20data%20processing n5:interpolation
n4:kodStatuVydavatele
DE - Spolková republika Německo
n4:kontrolniKodProRIV
[EDBAAFB59D4E]
n4:nazevZdroje
Medical and Biological Engineering and Computing
n4:obor
n11:FH
n4:pocetDomacichTvurcuVysledku
1
n4:pocetTvurcuVysledku
6
n4:rokUplatneniVysledku
n12:2014
n4:svazekPeriodika
52
n4:tvurceVysledku
Ťupa, Ondřej Yadollahi, Mohammadreza Vaseghi, Saeed Vyšata, Oldřich Mareš, Jan Procházka, Aleš
n4:wos
000333184200001
s:issn
0140-0118
s:numberOfPages
8
n16:doi
10.1007/s11517-013-1134-6
n14:organizacniJednotka
11150