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The Global Positioning System (GPS) revolutionized positioning on Earth, providing precise location data through satellite ranging. The GPS system was developed in 1978 by the U.S. Department of Defense  for military use, and it became available for civilian applications in 1983, transforming fields including navigation, fleet management, and time synchronization for telecommunications systems.GPS consists of satellites in medium Earth orbit, about 20,200 kilometers above the surface,...
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Determining Basal Energy Expenditure and the Capacity of Thermogenic Adipocytes to Expend Energy in Obese Mice
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Complex Terrain Load Carriage Energy Expenditure Estimation Using Global Positioning System Devices.

Adam W Potter1,2, William R Santee1,3, Stephen P Mullen1

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|June 27, 2018
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Accurately estimating energy expenditure (EE) during military load carriage is challenging. The Pandolf-Santee equation using Global Positioning System (GPS) data provides a reliable method for tracking EE in complex terrains.

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Area of Science:

  • Exercise physiology
  • Biomechanics
  • Wearable technology

Background:

  • Military load carriage significantly increases energy expenditure (EE), posing challenges for accurate estimation due to varied terrain.
  • Global Positioning System (GPS) devices offer potential for tracking movement but face limitations with the delayed physiological response.
  • Investigating GPS-based equations is crucial for precise EE assessment in demanding operational environments.

Purpose of the Study:

  • To evaluate the accuracy of three distinct equations in estimating EE during complex terrain load carriage using GPS data.
  • To compare GPS-derived EE estimates with measurements from a mobile metabolic sensor.

Main Methods:

  • Twelve active duty military personnel completed multiple trials on a complex terrain trail under varying load conditions.
  • Energy expenditure was calculated using the Pandolf-Santee equation, the de Müllenheim equation, and the Minimum Mechanics model, with GPS data as input.
  • Minute-by-minute EE estimates were exponentially smoothed and compared against mobile metabolic sensor data.

Main Results:

  • The Pandolf-Santee equation demonstrated no significant bias in EE estimation (-2 ± 12 W).
  • The de Müllenheim equation showed a significant positive bias (38 ± 13 W), while the Minimum Mechanics model exhibited a significant negative bias (-101 ± 7 W).

Conclusions:

  • The Pandolf-Santee equation is a validated tool for accurate EE estimation from GPS data during load carriage.
  • Utilizing an exponential smoothing factor of 0.5 enhances the precision of EE tracking during non-steady-state exercise conditions.