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Validating an advanced smartphone application for thermal advising in cold environments
The ClimApp smartphone application was developed to merge meteorological forecast data with personal information for individualized and improved thermal warning during heat and cold stress and for indoor comfort in buildings. For cold environments, ClimApp predicts the personal thermal stress and st...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10643309/ https://www.ncbi.nlm.nih.gov/pubmed/37833565 http://dx.doi.org/10.1007/s00484-023-02553-w |
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author | Eggeling, Jakob Rydenfält, Christofer Halder, Amitava Toftum, Jørn Nybo, Lars Kingma, Boris Gao, Chuansi |
author_facet | Eggeling, Jakob Rydenfält, Christofer Halder, Amitava Toftum, Jørn Nybo, Lars Kingma, Boris Gao, Chuansi |
author_sort | Eggeling, Jakob |
collection | PubMed |
description | The ClimApp smartphone application was developed to merge meteorological forecast data with personal information for individualized and improved thermal warning during heat and cold stress and for indoor comfort in buildings. For cold environments, ClimApp predicts the personal thermal stress and strain by the use of the Insulation REQuired model that combines weather and personal physiological data with additional consideration of the Wind Chill index based on the local weather forecast. In this study, we validated the individualized ClimApp index relative to measurements and compared it with the Universal Temperature Climate Index (UTCI). To this aim, 55 participants (27 females) were exposed to at least 1 h in an outdoor environment of 10 °C or below (average 1.4 °C air temperature, 74.9% relative humidity, and 4.7 m/s air velocity) inputting their activity level and clothing insulation as instructed by ClimApp. The UTCI and ClimApp indices were calculated and compared to the participants’ perceived thermal sensation. The ClimApp index root mean square deviation (RMSD) was below the standard deviation of the perceived thermal sensation which indicates a valid prediction and the UTCI RMSD was higher than the standard deviation which indicates an invalid prediction. The correlation of ClimApp and UTCI to the perceived thermal sensation was statistically significant for both models. |
format | Online Article Text |
id | pubmed-10643309 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-106433092023-11-14 Validating an advanced smartphone application for thermal advising in cold environments Eggeling, Jakob Rydenfält, Christofer Halder, Amitava Toftum, Jørn Nybo, Lars Kingma, Boris Gao, Chuansi Int J Biometeorol Original Paper The ClimApp smartphone application was developed to merge meteorological forecast data with personal information for individualized and improved thermal warning during heat and cold stress and for indoor comfort in buildings. For cold environments, ClimApp predicts the personal thermal stress and strain by the use of the Insulation REQuired model that combines weather and personal physiological data with additional consideration of the Wind Chill index based on the local weather forecast. In this study, we validated the individualized ClimApp index relative to measurements and compared it with the Universal Temperature Climate Index (UTCI). To this aim, 55 participants (27 females) were exposed to at least 1 h in an outdoor environment of 10 °C or below (average 1.4 °C air temperature, 74.9% relative humidity, and 4.7 m/s air velocity) inputting their activity level and clothing insulation as instructed by ClimApp. The UTCI and ClimApp indices were calculated and compared to the participants’ perceived thermal sensation. The ClimApp index root mean square deviation (RMSD) was below the standard deviation of the perceived thermal sensation which indicates a valid prediction and the UTCI RMSD was higher than the standard deviation which indicates an invalid prediction. The correlation of ClimApp and UTCI to the perceived thermal sensation was statistically significant for both models. Springer Berlin Heidelberg 2023-10-14 2023 /pmc/articles/PMC10643309/ /pubmed/37833565 http://dx.doi.org/10.1007/s00484-023-02553-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Paper Eggeling, Jakob Rydenfält, Christofer Halder, Amitava Toftum, Jørn Nybo, Lars Kingma, Boris Gao, Chuansi Validating an advanced smartphone application for thermal advising in cold environments |
title | Validating an advanced smartphone application for thermal advising in cold environments |
title_full | Validating an advanced smartphone application for thermal advising in cold environments |
title_fullStr | Validating an advanced smartphone application for thermal advising in cold environments |
title_full_unstemmed | Validating an advanced smartphone application for thermal advising in cold environments |
title_short | Validating an advanced smartphone application for thermal advising in cold environments |
title_sort | validating an advanced smartphone application for thermal advising in cold environments |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10643309/ https://www.ncbi.nlm.nih.gov/pubmed/37833565 http://dx.doi.org/10.1007/s00484-023-02553-w |
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