Using a Contemporary Portable Metabolic Gas Exchange System for Assessing Energy Expenditure: A Validity and Reliability Study.

There are several methods available to assess energy expenditure, all associated with inherent pros and cons that must be adequately considered for use in specific environments and populations. A requirement of all methods is that they must be valid and reliable in their capability to accurately measure oxygen consumption (VO2) and carbon dioxide production (VCO2). The purpose of this study was to evaluate the reliability and validity of the mobile CO2/O2 Breath and Respiration Analyzer (COBRA) relative to a criterion system (Parvomedics TrueOne 2400®, PARVO) with additional measurements to compare the COBRA to a portable system (Vyaire Medical, Oxycon Mobile®, OXY). Fourteen volunteers with a mean of 24 years old, body weight of 76 kg, and a VO2peak of 3.8 L∙min-1 performed four repeated trials of progressive exercises. Simultaneous steady-state measurements of VO2, VCO2, and minute ventilation (VE) by the COBRA/PARVO and OXY systems were conducted at rest, while walking (23-36% VO2peak), jogging (49-67% VO2peak), and running (60-76% VO2peak). Data collection was randomized by the order of system tested (COBRA/PARVO and OXY) and was standardized to maintain work intensity (rest to run) progression across study trials and days (two trials/day over two days). Systematic bias was examined to assess the accuracy of the COBRA to PARVO and OXY to PARVO across work intensities. Intra- and inter-unit variability were assessed with interclass correlation coefficients (ICC) and a 95% limit of agreement intervals. The COBRA and PARVO produced similar measures for VO2 (Bias ± SD, 0.01 ± 0.13 L·min-1; 95% LoA, (-0.24, 0.27 L·min-1); R2 = 0.982), VCO2 (0.06 ± 0.13 L·min-1; (-0.19, 0.31 L·min-1); R2 = 0.982), VE (2.07 ± 2.76 L·min-1; (-3.35, 7.49 L·min-1); R2 = 0.991) across work intensities. There was a linear bias across both the COBRA and OXY with increased work intensity. The coefficient of variation for the COBRA ranged from 7 to 9% across measures for VO2, VCO2, and VE. COBRA was reliable across measurements for VO2 (ICC = 0.825; 0.951), VCO2 (ICC = 0.785; 0.876), and VE (ICC = 0.857; 0.945) for intra-unit reliability, respectively. The COBRA is an accurate and reliable mobile system for measuring gas exchange at rest and across a range of work intensities.

Measured body composition and geometrical data of four "virtual family" members for thermoregulatory modeling.

The purpose of this paper is to develop a database of tissue composition, distribution, volume, surface area, and skin thickness from anatomically correct human models, the virtual family. These models were based on high-resolution magnetic resonance imaging (MRI) of human volunteers, including two adults (male and female) and two children (boy and girl). In the segmented image dataset, each voxel is associated with a label which refers to a tissue type that occupies up that specific cubic millimeter of the body. The tissue volume was calculated from the number of the voxels with the same label. Volumes of 24 organs in body and volumes of 7 tissues in 10 specific body regions were calculated. Surface area was calculated from the collection of voxels that are touching the exterior air. Skin thicknesses were estimated from its volume and surface area. The differences between the calculated and original masses were about 3 % or less for tissues or organs that are important to thermoregulatory modeling, e.g., muscle, skin, and fat. This accurate database of body tissue distributions and geometry is essential for the development of human thermoregulatory models. Data derived from medical imaging provide new effective tools to enhance thermal physiology research and gain deeper insight into the mechanisms of how the human body maintains heat balance.

Complex Terrain Load Carriage Energy Expenditure Estimation Using Global Positioning System Devices.

INTRODUCTION: Military load carriage can cause extreme energy expenditure (EE) that is difficult to estimate due to complex terrain grades and surfaces. Global Positioning System (GPS) devices capture rapid changes in walking speed and terrain but the delayed respiratory response to movement is problematic. We investigated the accuracy using GPS data in three different equations to estimate EE during complex terrain load carriage. METHODS: Twelve active duty military personnel (age, 20 ± 3 yr; height, 174 ± 8 cm; body mass, 85 ± 13 kg) hiked a complex terrain trail on multiple visits under different external load conditions. Energy expenditure was estimated by inputting GPS data into three different equations: the Pandolf-Santee equation, a recent GPS-based equation from de Müllenheim et al.; and the Minimum Mechanics model. Minute-by-minute EE estimates were exponentially smoothed using smoothing factors between 0.05 and 0.95 and compared with mobile metabolic sensor EE measurements. RESULTS: The Pandolf-Santee equation had no significant estimation bias (-2 ± 12 W; P = 0.89). Significant biases were detected for the de Müllenheim equation (38 ± 13 W; P = 0.004) and the Minimum Mechanics model (-101 ± 7 W; P < 0.001). CONCLUSIONS: Energy expenditure can be accurately estimated from GPS data using the Pandolf-Santee equation. Applying a basic exponential smoothing factor of 0.5 to GPS data enables more precise tracking of EE during non-steady-state exercise.

Metabolic Costs of Military Load Carriage over Complex Terrain.

INTRODUCTION: Dismounted military operations often involve prolonged load carriage over complex terrain, which can result in excessive metabolic costs that can directly impair soldiers' performance. Although estimating these demands is a critical interest for mission planning purposes, it is unclear whether existing estimation equations developed from controlled laboratory- and field-based studies accurately account for energy costs of traveling over complex terrain. This study investigated the accuracy of the following equations for military populations when applied to data collected over complex terrain with two different levels of load carriage: American College of Sports Medicine (2002), Givoni and Goldman (1971), Jobe and White (2009), Minetti et al (2002), Pandolf et al (1977), and Santee et al (2003). MATERIALS AND METHODS: Nine active duty military personnel (age 21 ± 3 yr; height 1.72 ± 0.07 m; body mass 83.4 ± 12.9 kg; VO2 max 47.8 ± 3.9 mL/kg/min) were monitored during load carriage (with loads equal to 30% and 45% of body mass) over a 10-km mixed terrain course on two separate test days. The course was divided into four 2.5-km laps of 40 segments based on distance, grade, and/or surface factors. Timing gates and radio-frequency identification cards (SportIdent; Scarborough Orienteering, Huntington Beach, CA) were used to record completion times for each course segment. Breath-by-breath measures of energy expenditure were collected using portable oxygen exchange devices (COSMED Sri., Rome, Italy) and compared model estimates. RESULTS: The Santee et al equation performed best, demonstrating the smallest estimation bias (-13 ± 87 W) and lowest root mean square error (99 W). CONCLUSION: Current predictive equations underestimate the metabolic cost of load carriage by military personnel over complex terrain. Applying the Santee et al correction factor to the Pandolf et al equation may be the most suitable approach for estimating metabolic demands in these circumstances. However, this work also outlines the need for improvements to these methods, new method development and validation, or the use of a multi-model approach to account for mixed terrain.