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Addressing the unresolved challenge of quantifying skiing exposure—A proof of concept using smartphone sensors

In epidemiological studies related to winter sports, especially alpine skiing, an unresolved methodological challenge is the quantification of actual on-snow activity exposure. Such information would be relevant for reporting meaningful measures of injury incidence, which refers to the number of new...

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Autores principales: Meinke, Anita, Spörri, Jörg, Brogli, Luzius, Schwab, Patrick, Karlen, Walter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10203200/
https://www.ncbi.nlm.nih.gov/pubmed/37229363
http://dx.doi.org/10.3389/fspor.2023.1157987
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author Meinke, Anita
Spörri, Jörg
Brogli, Luzius
Schwab, Patrick
Karlen, Walter
author_facet Meinke, Anita
Spörri, Jörg
Brogli, Luzius
Schwab, Patrick
Karlen, Walter
author_sort Meinke, Anita
collection PubMed
description In epidemiological studies related to winter sports, especially alpine skiing, an unresolved methodological challenge is the quantification of actual on-snow activity exposure. Such information would be relevant for reporting meaningful measures of injury incidence, which refers to the number of new injuries that occur in a given population and time period. Accordingly, accurate determination of the denominator, i.e., actual “activity exposure time”, is critical for injury surveillance and reporting. In this perspective article, we explore the question of whether wearable sensors in combination with mHealth applications are suitable tools to accurately quantify the periods in a ski day when the skier is physically skiing and not resting or using a mechanical means of transport. As a first proof of concept, we present exemplary data from a youth competitive alpine skier who wore his smartphone with embedded sensors on his body on several ski days during one winter season. We compared these data to self-reported estimates of ski exposure, as used in athletes' training diaries. In summary, quantifying on-snow activity exposure in alpine skiing using sensor data from smartphones is technically feasible. For example, the sensors could be used to track ski training sessions, estimate the actual time spent skiing, and even quantify the number of runs and turns made as long as the smartphone is worn. Such data could be very useful in determining actual exposure time in the context of injury surveillance and could prove valuable for effective stress management and injury prevention in athletes.
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spelling pubmed-102032002023-05-24 Addressing the unresolved challenge of quantifying skiing exposure—A proof of concept using smartphone sensors Meinke, Anita Spörri, Jörg Brogli, Luzius Schwab, Patrick Karlen, Walter Front Sports Act Living Sports and Active Living In epidemiological studies related to winter sports, especially alpine skiing, an unresolved methodological challenge is the quantification of actual on-snow activity exposure. Such information would be relevant for reporting meaningful measures of injury incidence, which refers to the number of new injuries that occur in a given population and time period. Accordingly, accurate determination of the denominator, i.e., actual “activity exposure time”, is critical for injury surveillance and reporting. In this perspective article, we explore the question of whether wearable sensors in combination with mHealth applications are suitable tools to accurately quantify the periods in a ski day when the skier is physically skiing and not resting or using a mechanical means of transport. As a first proof of concept, we present exemplary data from a youth competitive alpine skier who wore his smartphone with embedded sensors on his body on several ski days during one winter season. We compared these data to self-reported estimates of ski exposure, as used in athletes' training diaries. In summary, quantifying on-snow activity exposure in alpine skiing using sensor data from smartphones is technically feasible. For example, the sensors could be used to track ski training sessions, estimate the actual time spent skiing, and even quantify the number of runs and turns made as long as the smartphone is worn. Such data could be very useful in determining actual exposure time in the context of injury surveillance and could prove valuable for effective stress management and injury prevention in athletes. Frontiers Media S.A. 2023-05-09 /pmc/articles/PMC10203200/ /pubmed/37229363 http://dx.doi.org/10.3389/fspor.2023.1157987 Text en © 2023 Meinke, Spörri, Brogli, Schwab and Karlen. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (https://creativecommons.org/licenses/by/4.0/) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Sports and Active Living
Meinke, Anita
Spörri, Jörg
Brogli, Luzius
Schwab, Patrick
Karlen, Walter
Addressing the unresolved challenge of quantifying skiing exposure—A proof of concept using smartphone sensors
title Addressing the unresolved challenge of quantifying skiing exposure—A proof of concept using smartphone sensors
title_full Addressing the unresolved challenge of quantifying skiing exposure—A proof of concept using smartphone sensors
title_fullStr Addressing the unresolved challenge of quantifying skiing exposure—A proof of concept using smartphone sensors
title_full_unstemmed Addressing the unresolved challenge of quantifying skiing exposure—A proof of concept using smartphone sensors
title_short Addressing the unresolved challenge of quantifying skiing exposure—A proof of concept using smartphone sensors
title_sort addressing the unresolved challenge of quantifying skiing exposure—a proof of concept using smartphone sensors
topic Sports and Active Living
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10203200/
https://www.ncbi.nlm.nih.gov/pubmed/37229363
http://dx.doi.org/10.3389/fspor.2023.1157987
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