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Remote physiological and GPS data processing in evaluation of physical activities
Aleš Procházka1, Saeed Vaseghi, Mohammadreza Yadollahi
1Department of Computing and Control Engineering, Institute of Chemical Technology in Prague, 166 28, Prague, Czech Republic, A.Prochazka@ieee.org.
Medical & Biological Engineering & Computing
|December 25, 2013
Summary
This study analyzed cycling data using global positioning system (GPS) and heart rate monitors. It found a 7.5-second delay between heart rate changes and altitude gradients, which decreased during training.
Area of Science:
- Sports Science
- Biomedical Engineering
- Data Science
Background:
- Global Positioning System (GPS) and remote physiological sensors generate valuable data for analyzing physical activities.
- Understanding the relationship between physiological responses and environmental factors in cycling is crucial for performance optimization.
Purpose of the Study:
- To analyze physical activities during cycling by correlating heart rate and altitude gradient data.
- To develop and apply an algorithm using cross-correlations to determine the time delay between heart rate and altitude changes.
Main Methods:
- Utilized a database of data from GPS receivers and physiological sensors collected over 22 identical cycling routes (approx. 130 km each).
- Applied statistical and digital signal processing techniques, including error rejection, interpolation, digital filtering, and cross-correlation analysis.
- Estimated the time delay between changes in heart rate and altitude gradient using regression analysis.
Main Results:
- Identified an average time delay of approximately 7.5 seconds between heart rate changes and altitude gradient.
- Observed a decrease in this time delay over the course of each training route, indicating physiological adaptation.
Conclusions:
- The proposed cross-correlation algorithm effectively quantifies the relationship between heart rate and altitude gradient in cycling.
- The findings provide insights into the physiological responses of cyclists to varying terrain and suggest potential for performance monitoring and training adjustments.
