Using GPS, accelerometry and heart rate to predict outdoor graded walking energy expenditure

Area of Science:

• Exercise Physiology
• Biomedical Engineering
• Wearable Technology

Background:

• Accurate estimation of energy expenditure (EE) is crucial for health and performance monitoring.
• Outdoor walking, a common physical activity, presents unique challenges for EE measurement due to variable terrain and speed.
• Existing methods like accelerometry and heart rate monitors have limitations in accuracy during diverse walking conditions.

Purpose of the Study:

• To compare the accuracy of Global Positioning System (GPS), accelerometry, and heart rate (HR) monitoring for estimating EE during outdoor walking.
• To identify the optimal method or combination of methods for various walking conditions, including level, uphill, and downhill.
• To provide evidence-based recommendations for selecting the most effective technology for EE assessment in real-world walking scenarios.

Main Methods:

• Thirty adults participated in outdoor walking trials at different speeds (2.0, 3.5, 5.0 km/h) on level, 3.4% uphill, and 10.4% downhill gradients.
• Energy expenditure (EE) was measured using a portable metabolic system (K4b²).
• Participants simultaneously wore GPS, accelerometer, and HR monitor devices to collect data for analysis using linear mixed models (LMMs).

Main Results:

• Global Positioning System (GPS) demonstrated the highest accuracy in estimating EE across level, uphill, and downhill walking conditions.
• GPS accuracy was comparable to accelerometry during level walking but superior on graded inclines.
• Combining different methods did not significantly improve the accuracy of EE estimation beyond using GPS alone.

Conclusions:

• Global Positioning System (GPS) is the most accurate and reliable method for estimating energy expenditure during outdoor walking, particularly on varied terrain.
• The findings support the use of GPS technology for objective and precise EE assessment in free-living walking environments.
• This study offers valuable insights for selecting appropriate wearable technologies and equations for accurate EE monitoring in diverse outdoor walking activities.