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一款根据 ISO 7933:2018 预测热应激的免费软件。

A free software to predict heat strain according to the ISO 7933:2018.

机构信息

FAME Laboratory, School of Exercise Science, University of Thessaly, Greece.

出版信息

Ind Health. 2019 Nov 29;57(6):711-720. doi: 10.2486/indhealth.2018-0216. Epub 2019 Mar 27.

DOI:10.2486/indhealth.2018-0216
PMID:30918161
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6885605/
Abstract

Our primary objective in this study was to design and implement the FAME Lab PHS Calculator software (PHS) (www.famelab.gr/research/downloads), a free tool to calculate the predicted heat strain of an individual based on ISO 7933:2018. Our secondary objective was to optimize the practicality of the PHS by incorporating knowledge from other ISO standards and published literature. The third objective of this study was to assess: (i) the criterion-related validity of the PHS by comparing its results against those obtained using the original ISO 7933:2018 code; and (ii) the construct validity of the PHS by comparing its results against those obtained via field experiments performed in human participants during work in the heat. Our analysis for criterion validity demonstrates that PHS provides valid results within the required computational accuracy, according to Annex F of ISO 7933:2018. The construct validity showed that root mean square errors (RMSE) and 95% limits of agreement (LOA) were minimal between measured and predicted core temperature (RMSE: 0.3°C; LOA: 0.06 ± 0.58°C) and small between measured and predicted mean skin temperature (RMSE: 1.1°C; LOA: 0.59 ± 1.83°C). In conclusion, the PHS software demonstrated strong criterion-related and construct-related validity.

摘要

本研究的主要目的是设计和实现 FAME 实验室 PHS 计算器软件(PHS)(www.famelab.gr/research/downloads),这是一个免费的工具,可以根据 ISO 7933:2018 计算个体的预测热应激。我们的次要目标是通过纳入其他 ISO 标准和已发表文献的知识来优化 PHS 的实用性。本研究的第三个目标是评估:(i) 通过将 PHS 的结果与原始 ISO 7933:2018 代码的结果进行比较,评估 PHS 的准则相关性有效性;(ii) 通过将 PHS 的结果与在热环境中进行人体参与者的现场实验获得的结果进行比较,评估 PHS 的构念有效性。我们的准则有效性分析表明,根据 ISO 7933:2018 的附件 F,PHS 在所需的计算精度内提供了有效的结果。构念有效性表明,实测核心温度与预测核心温度之间的均方根误差(RMSE)和 95%一致性界限(LOA)最小(RMSE:0.3°C;LOA:0.06 ± 0.58°C),实测与预测平均皮肤温度之间的 RMSE 也较小(RMSE:1.1°C;LOA:0.59 ± 1.83°C)。总之,PHS 软件表现出很强的准则相关性和构念相关性有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4201/6885605/2fc79ff93377/indhealth-57-711-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4201/6885605/992c561a6d10/indhealth-57-711-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4201/6885605/602d64a65709/indhealth-57-711-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4201/6885605/ced1e258fb74/indhealth-57-711-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4201/6885605/2fc79ff93377/indhealth-57-711-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4201/6885605/992c561a6d10/indhealth-57-711-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4201/6885605/602d64a65709/indhealth-57-711-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4201/6885605/ced1e258fb74/indhealth-57-711-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4201/6885605/2fc79ff93377/indhealth-57-711-g004.jpg

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