Remote physiological and GPS data processing in evaluation of physical activities
Language English Country United States Media print-electronic
Document type Journal Article, Research Support, Non-U.S. Gov't
- MeSH
- Algorithms MeSH
- Bicycling physiology MeSH
- Geographic Information Systems * MeSH
- Humans MeSH
- Signal Processing, Computer-Assisted * MeSH
- Regression Analysis MeSH
- Heart Rate physiology MeSH
- Telemetry methods MeSH
- Geography MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
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.
See more in PubMed
Med Sci Sports Exerc. 2007 May;39(5):822-9 PubMed
Int J Sports Med. 2008 Feb;29(2):129-33 PubMed
Motion Assessment for Accelerometric and Heart Rate Cycling Data Analysis
