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Augmented-reality swim goggles accurately and reliably measure swim performance metrics in recreational swimmers

BACKGROUND: Swimmers commonly access performance metrics such as lap splits, distance, and pacing information between work bouts while they rest. Recently, a new category of tracking devices for swimming was introduced with the FORM Smart Swim Goggles (FORM Goggles). The goggles have a built-in see-...

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Autores principales: Eisenhardt, Dan, Kits, Aidan, Madeleine, Pascal, Samani, Afshin, Clarke, David C., Kristiansen, Mathias
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10304285/
https://www.ncbi.nlm.nih.gov/pubmed/37389272
http://dx.doi.org/10.3389/fspor.2023.1188102
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author Eisenhardt, Dan
Kits, Aidan
Madeleine, Pascal
Samani, Afshin
Clarke, David C.
Kristiansen, Mathias
author_facet Eisenhardt, Dan
Kits, Aidan
Madeleine, Pascal
Samani, Afshin
Clarke, David C.
Kristiansen, Mathias
author_sort Eisenhardt, Dan
collection PubMed
description BACKGROUND: Swimmers commonly access performance metrics such as lap splits, distance, and pacing information between work bouts while they rest. Recently, a new category of tracking devices for swimming was introduced with the FORM Smart Swim Goggles (FORM Goggles). The goggles have a built-in see-through display and are capable of tracking and displaying distance, time splits, stroke, and pace metrics in real time using machine learning and augmented reality through a heads-up display. The purpose of this study was to assess the validity and reliability of the FORM Goggles compared with video analysis for stroke type, pool length count, pool length time, stroke rate, and stroke count in recreational swimmers and triathletes. METHOD: A total of 36 participants performed mixed swimming intervals in a 25-m pool across two identical 900-m swim sessions performed at comparable intensities with 1 week interval. The participants wore FORM Goggles during their swims, which detected the following five swim metrics: stroke type, pool length time, pool length count, stroke count, and stroke rate. Four video cameras were positioned on the pool edges to capture ground truth video footage, which was then manually labeled by three trained individuals. Mean (SD) differences between FORM Goggles and ground truth were calculated for the selected metrics for both sessions. The absolute mean difference and mean absolute percentage error were used to assess the differences of the FORM Goggles relative to ground truth. The test–retest reliability of the goggles was assessed using both relative and absolute reliability metrics. RESULTS: Compared with video analysis, the FORM Goggles identified the correct stroke type at a rate of 99.7% (N = 2,354 pool lengths, p < 0.001), pool length count accuracy of 99.8%, and mean differences (FORM Goggles–ground truth) for pool length time: −0.10 s (1.49); stroke count: −0.63 (1.82); and stroke rate: 0.19 strokes/min (3.23). The test–retest intra-class correlation coefficient (ICC) values between the two test days were 0.793 for pool length time, 0.797 for stroke count, and 0.883 for stroke rate. Overall, for pool length time, the residuals were within ±1.0s for 65.3% of the total pool lengths, for stroke count within ±1 stroke for 62.6% of the total pool lengths, and for stroke rate within ±2 strokes/min for 66.40% of the total pool lengths. CONCLUSION: The FORM Goggles were found valid and reliable for the tracking of pool length time, pool length count, stroke count, stroke rate, and stroke type during freestyle, backstroke, and breaststroke swimming in recreational swimmers and triathletes when compared with video analysis. This opens perspectives for receiving real-time information on performance metrics during swimming.
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spelling pubmed-103042852023-06-29 Augmented-reality swim goggles accurately and reliably measure swim performance metrics in recreational swimmers Eisenhardt, Dan Kits, Aidan Madeleine, Pascal Samani, Afshin Clarke, David C. Kristiansen, Mathias Front Sports Act Living Sports and Active Living BACKGROUND: Swimmers commonly access performance metrics such as lap splits, distance, and pacing information between work bouts while they rest. Recently, a new category of tracking devices for swimming was introduced with the FORM Smart Swim Goggles (FORM Goggles). The goggles have a built-in see-through display and are capable of tracking and displaying distance, time splits, stroke, and pace metrics in real time using machine learning and augmented reality through a heads-up display. The purpose of this study was to assess the validity and reliability of the FORM Goggles compared with video analysis for stroke type, pool length count, pool length time, stroke rate, and stroke count in recreational swimmers and triathletes. METHOD: A total of 36 participants performed mixed swimming intervals in a 25-m pool across two identical 900-m swim sessions performed at comparable intensities with 1 week interval. The participants wore FORM Goggles during their swims, which detected the following five swim metrics: stroke type, pool length time, pool length count, stroke count, and stroke rate. Four video cameras were positioned on the pool edges to capture ground truth video footage, which was then manually labeled by three trained individuals. Mean (SD) differences between FORM Goggles and ground truth were calculated for the selected metrics for both sessions. The absolute mean difference and mean absolute percentage error were used to assess the differences of the FORM Goggles relative to ground truth. The test–retest reliability of the goggles was assessed using both relative and absolute reliability metrics. RESULTS: Compared with video analysis, the FORM Goggles identified the correct stroke type at a rate of 99.7% (N = 2,354 pool lengths, p < 0.001), pool length count accuracy of 99.8%, and mean differences (FORM Goggles–ground truth) for pool length time: −0.10 s (1.49); stroke count: −0.63 (1.82); and stroke rate: 0.19 strokes/min (3.23). The test–retest intra-class correlation coefficient (ICC) values between the two test days were 0.793 for pool length time, 0.797 for stroke count, and 0.883 for stroke rate. Overall, for pool length time, the residuals were within ±1.0s for 65.3% of the total pool lengths, for stroke count within ±1 stroke for 62.6% of the total pool lengths, and for stroke rate within ±2 strokes/min for 66.40% of the total pool lengths. CONCLUSION: The FORM Goggles were found valid and reliable for the tracking of pool length time, pool length count, stroke count, stroke rate, and stroke type during freestyle, backstroke, and breaststroke swimming in recreational swimmers and triathletes when compared with video analysis. This opens perspectives for receiving real-time information on performance metrics during swimming. Frontiers Media S.A. 2023-06-07 /pmc/articles/PMC10304285/ /pubmed/37389272 http://dx.doi.org/10.3389/fspor.2023.1188102 Text en © 2023 Eisenhardt, Kits, Madeleine, Samani, Clarke and Kristiansen. 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
Eisenhardt, Dan
Kits, Aidan
Madeleine, Pascal
Samani, Afshin
Clarke, David C.
Kristiansen, Mathias
Augmented-reality swim goggles accurately and reliably measure swim performance metrics in recreational swimmers
title Augmented-reality swim goggles accurately and reliably measure swim performance metrics in recreational swimmers
title_full Augmented-reality swim goggles accurately and reliably measure swim performance metrics in recreational swimmers
title_fullStr Augmented-reality swim goggles accurately and reliably measure swim performance metrics in recreational swimmers
title_full_unstemmed Augmented-reality swim goggles accurately and reliably measure swim performance metrics in recreational swimmers
title_short Augmented-reality swim goggles accurately and reliably measure swim performance metrics in recreational swimmers
title_sort augmented-reality swim goggles accurately and reliably measure swim performance metrics in recreational swimmers
topic Sports and Active Living
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10304285/
https://www.ncbi.nlm.nih.gov/pubmed/37389272
http://dx.doi.org/10.3389/fspor.2023.1188102
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