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A Muscle Load Feedback Application for Strength Training: A Proof-of-Concept Study
Muscle overload injuries in strength training might be prevented by providing personalized feedback about muscle load during a workout. In the present study, a new muscle load feedback application, which monitors and visualizes the loading of specific muscle groups, was developed in collaboration wi...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10534713/ https://www.ncbi.nlm.nih.gov/pubmed/37755847 http://dx.doi.org/10.3390/sports11090170 |
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author | Noteboom, Lisa Nijs, Anouk Beek, Peter J. van der Helm, Frans C. T. Hoozemans, Marco J. M. |
author_facet | Noteboom, Lisa Nijs, Anouk Beek, Peter J. van der Helm, Frans C. T. Hoozemans, Marco J. M. |
author_sort | Noteboom, Lisa |
collection | PubMed |
description | Muscle overload injuries in strength training might be prevented by providing personalized feedback about muscle load during a workout. In the present study, a new muscle load feedback application, which monitors and visualizes the loading of specific muscle groups, was developed in collaboration with the fitness company Gymstory. The aim of the present study was to examine the effectiveness of this feedback application in managing muscle load balance, muscle load level, and muscle soreness, and to evaluate how its actual use was experienced. Thirty participants were randomly distributed into ‘control’, ‘partial feedback’, and ‘complete feedback’ groups and monitored for eight workouts using the automatic exercise tracking system of Gymstory. The control group received no feedback, while the partial feedback group received a visualization of their estimated cumulative muscle load after each exercise, and the participants in the complete feedback group received this visualization together with suggestions for the next exercise to target muscle groups that had not been loaded yet. Generalized estimation equations (GEEs) were used to compare muscle load balance and soreness, and a one-way ANOVA was used to compare user experience scores between groups. The complete feedback group showed a significantly better muscle load balance (β = −18.9; 95% CI [−29.3, −8.6]), adhered better to the load suggestion provided by the application (significant interactions), and had higher user experience scores for Attractiveness (p = 0.036), Stimulation (p = 0.031), and Novelty (p = 0.019) than the control group. No significant group differences were found for muscle soreness. Based on these results, it was concluded that personal feedback about muscle load in the form of a muscle body map in combination with exercise suggestions can effectively guide strength training practitioners towards certain load levels and more balanced cumulative muscle loads. This application has potential to be applied in strength training practice as a training tool and may help in preventing muscle overload. |
format | Online Article Text |
id | pubmed-10534713 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-105347132023-09-29 A Muscle Load Feedback Application for Strength Training: A Proof-of-Concept Study Noteboom, Lisa Nijs, Anouk Beek, Peter J. van der Helm, Frans C. T. Hoozemans, Marco J. M. Sports (Basel) Article Muscle overload injuries in strength training might be prevented by providing personalized feedback about muscle load during a workout. In the present study, a new muscle load feedback application, which monitors and visualizes the loading of specific muscle groups, was developed in collaboration with the fitness company Gymstory. The aim of the present study was to examine the effectiveness of this feedback application in managing muscle load balance, muscle load level, and muscle soreness, and to evaluate how its actual use was experienced. Thirty participants were randomly distributed into ‘control’, ‘partial feedback’, and ‘complete feedback’ groups and monitored for eight workouts using the automatic exercise tracking system of Gymstory. The control group received no feedback, while the partial feedback group received a visualization of their estimated cumulative muscle load after each exercise, and the participants in the complete feedback group received this visualization together with suggestions for the next exercise to target muscle groups that had not been loaded yet. Generalized estimation equations (GEEs) were used to compare muscle load balance and soreness, and a one-way ANOVA was used to compare user experience scores between groups. The complete feedback group showed a significantly better muscle load balance (β = −18.9; 95% CI [−29.3, −8.6]), adhered better to the load suggestion provided by the application (significant interactions), and had higher user experience scores for Attractiveness (p = 0.036), Stimulation (p = 0.031), and Novelty (p = 0.019) than the control group. No significant group differences were found for muscle soreness. Based on these results, it was concluded that personal feedback about muscle load in the form of a muscle body map in combination with exercise suggestions can effectively guide strength training practitioners towards certain load levels and more balanced cumulative muscle loads. This application has potential to be applied in strength training practice as a training tool and may help in preventing muscle overload. MDPI 2023-09-05 /pmc/articles/PMC10534713/ /pubmed/37755847 http://dx.doi.org/10.3390/sports11090170 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Noteboom, Lisa Nijs, Anouk Beek, Peter J. van der Helm, Frans C. T. Hoozemans, Marco J. M. A Muscle Load Feedback Application for Strength Training: A Proof-of-Concept Study |
title | A Muscle Load Feedback Application for Strength Training: A Proof-of-Concept Study |
title_full | A Muscle Load Feedback Application for Strength Training: A Proof-of-Concept Study |
title_fullStr | A Muscle Load Feedback Application for Strength Training: A Proof-of-Concept Study |
title_full_unstemmed | A Muscle Load Feedback Application for Strength Training: A Proof-of-Concept Study |
title_short | A Muscle Load Feedback Application for Strength Training: A Proof-of-Concept Study |
title_sort | muscle load feedback application for strength training: a proof-of-concept study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10534713/ https://www.ncbi.nlm.nih.gov/pubmed/37755847 http://dx.doi.org/10.3390/sports11090170 |
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