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Field validation of The Heat Strain Decision Aid during military load carriage.

Authors :
Waldock KAM
Lee BJ
Powell S
Wardle SL
Blacker SD
Myers SD
Maroni TD
Walker FS
Looney DP
Greeves JP
Potter AW
Source :
Computers in biology and medicine [Comput Biol Med] 2021 Jul; Vol. 134, pp. 104506. Date of Electronic Publication: 2021 May 20.
Publication Year :
2021

Abstract

Objectives: We aimed to determine the agreement between actual and predicted core body temperature, using the Heat Strain Decision Aid (HSDA), in non-Ground Close Combat (GCC) personnel wearing multi terrain pattern clothing during two stages of load carriage in temperate conditions.<br />Design: Cross-sectional.<br />Methods: Sixty participants (men = 49, women = 11, age 31 ± 8 years; height 171.1 ± 9.0 cm; body mass 78.1 ± 11.5 kg) completed two stages of load carriage, of increasing metabolic rate, as part of the development of new British Army physical employment standards (PES). An ingestible gastrointestinal sensor was used to measure core temperature. Testing was completed in wet bulb globe temperature conditions; 1.2-12.6 °C. Predictive accuracy and precision were analysed using individual and group mean inputs. Assessments were evaluated by bias, limits of agreement (LoA), mean absolute error (MAE), and root mean square error (RMSE). Accuracy was evaluated using a prediction bias of ±0.27 °C and by comparing predictions to the standard deviation of the actual core temperature.<br />Results: Modelling individual predictions provided an acceptable level of accuracy based on bias criterion; where the total of all trials bias ± LoA was 0.08 ± 0.82 °C. Predicted values were in close agreement with the actual data: MAE 0.37 °C and RMSE 0.46 °C for the collective data. Modelling using group mean inputs were less accurate than using individual inputs, but within the mean observed.<br />Conclusion: The HSDA acceptably predicts core temperature during load carriage to the new British Army non-GCC PES, in temperate conditions.<br /> (Copyright © 2021. Published by Elsevier Ltd.)

Details

Language :
English
ISSN :
1879-0534
Volume :
134
Database :
MEDLINE
Journal :
Computers in biology and medicine
Publication Type :
Academic Journal
Accession number :
34090016
Full Text :
https://doi.org/10.1016/j.compbiomed.2021.104506