How Precisely Can Easily Accessible Variables Predict Achilles and Patellar Tendon Forces during Running?

Patellar and Achilles tendinopathy commonly affect runners. Developing algorithms to predict cumulative force in these structures may help prevent these injuries. Importantly, such algorithms should be fueled with data that are easily accessible while completing a running session outside a biomechan...

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Autores principales:	René B. K. Brund, Rasmus Waagepetersen, Rasmus O. Nielsen, John Rasmussen, Michael S. Nielsen, Christian H. Andersen, Mark de Zee
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	Garmin wearables Achilles tendon patellar tendon algorithm injuries Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/bc107d253980414183a7fdc7a079f144
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spelling	oai:doaj.org-article:bc107d253980414183a7fdc7a079f1442021-11-11T19:20:11ZHow Precisely Can Easily Accessible Variables Predict Achilles and Patellar Tendon Forces during Running?10.3390/s212174181424-8220https://doaj.org/article/bc107d253980414183a7fdc7a079f1442021-11-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/21/7418https://doaj.org/toc/1424-8220Patellar and Achilles tendinopathy commonly affect runners. Developing algorithms to predict cumulative force in these structures may help prevent these injuries. Importantly, such algorithms should be fueled with data that are easily accessible while completing a running session outside a biomechanical laboratory. Therefore, the main objective of this study was to investigate whether algorithms can be developed for predicting patellar and Achilles tendon force and impulse during running using measures that can be easily collected by runners using commercially available devices. A secondary objective was to evaluate the predictive performance of the algorithms against the commonly used running distance. Trials of 24 recreational runners were collected with an Xsens suit and a Garmin Forerunner 735XT at three different intended running speeds. Data were analyzed using a mixed-effects multiple regression model, which was used to model the association between the estimated forces in anatomical structures and the training load variables during the fixed running speeds. This provides twelve algorithms for predicting patellar or Achilles tendon peak force and impulse per stride. The algorithms developed in the current study were always superior to the running distance algorithm.René B. K. BrundRasmus WaagepetersenRasmus O. NielsenJohn RasmussenMichael S. NielsenChristian H. AndersenMark de ZeeMDPI AGarticleGarminwearablesAchilles tendonpatellar tendonalgorithminjuriesChemical technologyTP1-1185ENSensors, Vol 21, Iss 7418, p 7418 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Garmin wearables Achilles tendon patellar tendon algorithm injuries Chemical technology TP1-1185
spellingShingle	Garmin wearables Achilles tendon patellar tendon algorithm injuries Chemical technology TP1-1185 René B. K. Brund Rasmus Waagepetersen Rasmus O. Nielsen John Rasmussen Michael S. Nielsen Christian H. Andersen Mark de Zee How Precisely Can Easily Accessible Variables Predict Achilles and Patellar Tendon Forces during Running?
description	Patellar and Achilles tendinopathy commonly affect runners. Developing algorithms to predict cumulative force in these structures may help prevent these injuries. Importantly, such algorithms should be fueled with data that are easily accessible while completing a running session outside a biomechanical laboratory. Therefore, the main objective of this study was to investigate whether algorithms can be developed for predicting patellar and Achilles tendon force and impulse during running using measures that can be easily collected by runners using commercially available devices. A secondary objective was to evaluate the predictive performance of the algorithms against the commonly used running distance. Trials of 24 recreational runners were collected with an Xsens suit and a Garmin Forerunner 735XT at three different intended running speeds. Data were analyzed using a mixed-effects multiple regression model, which was used to model the association between the estimated forces in anatomical structures and the training load variables during the fixed running speeds. This provides twelve algorithms for predicting patellar or Achilles tendon peak force and impulse per stride. The algorithms developed in the current study were always superior to the running distance algorithm.
format	article
author	René B. K. Brund Rasmus Waagepetersen Rasmus O. Nielsen John Rasmussen Michael S. Nielsen Christian H. Andersen Mark de Zee
author_facet	René B. K. Brund Rasmus Waagepetersen Rasmus O. Nielsen John Rasmussen Michael S. Nielsen Christian H. Andersen Mark de Zee
author_sort	René B. K. Brund
title	How Precisely Can Easily Accessible Variables Predict Achilles and Patellar Tendon Forces during Running?
title_short	How Precisely Can Easily Accessible Variables Predict Achilles and Patellar Tendon Forces during Running?
title_full	How Precisely Can Easily Accessible Variables Predict Achilles and Patellar Tendon Forces during Running?
title_fullStr	How Precisely Can Easily Accessible Variables Predict Achilles and Patellar Tendon Forces during Running?
title_full_unstemmed	How Precisely Can Easily Accessible Variables Predict Achilles and Patellar Tendon Forces during Running?
title_sort	how precisely can easily accessible variables predict achilles and patellar tendon forces during running?
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/bc107d253980414183a7fdc7a079f144
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How Precisely Can Easily Accessible Variables Predict Achilles and Patellar Tendon Forces during Running?

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