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Assessment Of Functional Baseline And Return To Play Criteria Using Gps Profile
OBJECTIVES: Return to play (RTP) are high following lower extremity injuries; however, objective sport specific clearance criteria are lacking. In ACL rehabilitation for example, current tests that are used such as single leg hop, isokinetic testing, and quad strength are not sport specific and do n...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8822101/ http://dx.doi.org/10.1177/2325967119S00441 |
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author | Moroski, Nathan M. Cain, E. Lyle Fleisig, Glenn S. |
author_facet | Moroski, Nathan M. Cain, E. Lyle Fleisig, Glenn S. |
author_sort | Moroski, Nathan M. |
collection | PubMed |
description | OBJECTIVES: Return to play (RTP) are high following lower extremity injuries; however, objective sport specific clearance criteria are lacking. In ACL rehabilitation for example, current tests that are used such as single leg hop, isokinetic testing, and quad strength are not sport specific and do not take fatigue into account. With the development of wearable GPS technologies (Catapult), there is great potential for the creation of objective RTP criteria. These GPS units provide objective validated data points in regards to athletes and their movements during games, training, or rehabilitation. It is reported over 1,500 teams across 35 sports, including NFL, NBA, MLB, and NCAA, are now using this technology. Teams have a vast amount of information, however, it is largely underutilized by the medical staff, and no standardized benchmarks exist. Using this data it was our goal to establish baseline benchmarks for a variety of data metrics and to begin to establish validated return to play criteria. METHODS: GPS records of a consecutive series of Division I NCAA football players were reviewed between 2015 and 2018. Ten metrics were gathered for healthy control players from eight positions (defensive back, wide receiver, running back, linebacker, tight-end, defensive line, offensive line, and quarter back. These metrics consisted of: total distance, total load, explosive yardage, explosive ratio, maximum velocity, inertial movement analysis (IMA) acceleration, IMA deceleration, change of direction (COD) left, and COD right. Average normal values were determined per session for healthy players. Overall we examined 198 player seasons data, 50 (DB), 37 (WR), 20 (RB), 47 (LB), 14 (TE) 14 (DL), 10 (OL), and 6 (QB) respectively. RESULTS: Healthy control averages for total distance was 5456.9 yards (DB), 4973.8 yards (WR), 4260.5 yards (RB), 4054.8 yards (LB), 4334.2 yards (TE), 3498.1 yards (DL), 3274.7 yards (OL), and 4199.2 yards (QB) respectively. Average total load was 492.8 (DB), 463.8 (WR), 393.0 (RB), 367.0 (LB), 423.9 (TE), 389.7 (DL), 381.2 (OL), and 410.8 (QB) respectively. Average explosive yardage was 472.7 (DB), 605.1 (WR), 454.5 (RB), 190.1 (LB), 320.7 (TE) 107.5 (DL), 70.6 (OL), and 191.8 (QB) respectively. Average explosive ratio was 0.847 (DB), 0.855 (WR), 1.045 (RB), 0.989 (LB), 0.985 (TE) 1.53 (DL), 1.31(OL), and 1.66 (QB) respectively. Average maximum velocity was 18.3 (DB), 17.2 (WR), 17.4 (RB), 15.7 (LB), 16.1 (TE) 13.7 (DL), 12.0 (OL), and 16.6 (QB) respectively. Average acceleration was 9.27 (DB), 8.53 (WR), 9.13 (RB), 9.78 (LB), 12.01 (TE) 21.7 (DL), 16.5 (OL), and 47.1 (QB) respectively. Average deceleration was 6.11 (DB), 4.02 (WR), 4.74 (RB), 6.11 (LB), 5.68 (TE) 8.79 (DL), 9.12 (OL), and 1.25 (QB) respectively. Average COD towards left was 6.55 (DB), 7.24 (WR), 9.09 (RB), 6.98 (LB), 9.38 (TE), 13.4 (DL), 11.3 (OL), and 8.22 (QB) respectively. Average COD towards right was 5.80 (DB), 6.45 (WR), 7.84 (RB), 5.91 (LB), 6.74 (TE) 12.5 (DL), 10.7 (OL), and 6.62 (QB) respectively. CONCLUSION: With the established healthy averages we now have a starting point for comparison of injured athletes and their rehabilitation progress. Categories most closely correlating with return to play following specific injuries is the next step. Additionally, this information may be used in injury prevention, detecting when an athlete may be overly fatigued and at great risk for injury. More data is needed to validate these numbers as well as establish criteria for healthy return to play. |
format | Online Article Text |
id | pubmed-8822101 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-88221012022-02-18 Assessment Of Functional Baseline And Return To Play Criteria Using Gps Profile Moroski, Nathan M. Cain, E. Lyle Fleisig, Glenn S. Orthop J Sports Med Article OBJECTIVES: Return to play (RTP) are high following lower extremity injuries; however, objective sport specific clearance criteria are lacking. In ACL rehabilitation for example, current tests that are used such as single leg hop, isokinetic testing, and quad strength are not sport specific and do not take fatigue into account. With the development of wearable GPS technologies (Catapult), there is great potential for the creation of objective RTP criteria. These GPS units provide objective validated data points in regards to athletes and their movements during games, training, or rehabilitation. It is reported over 1,500 teams across 35 sports, including NFL, NBA, MLB, and NCAA, are now using this technology. Teams have a vast amount of information, however, it is largely underutilized by the medical staff, and no standardized benchmarks exist. Using this data it was our goal to establish baseline benchmarks for a variety of data metrics and to begin to establish validated return to play criteria. METHODS: GPS records of a consecutive series of Division I NCAA football players were reviewed between 2015 and 2018. Ten metrics were gathered for healthy control players from eight positions (defensive back, wide receiver, running back, linebacker, tight-end, defensive line, offensive line, and quarter back. These metrics consisted of: total distance, total load, explosive yardage, explosive ratio, maximum velocity, inertial movement analysis (IMA) acceleration, IMA deceleration, change of direction (COD) left, and COD right. Average normal values were determined per session for healthy players. Overall we examined 198 player seasons data, 50 (DB), 37 (WR), 20 (RB), 47 (LB), 14 (TE) 14 (DL), 10 (OL), and 6 (QB) respectively. RESULTS: Healthy control averages for total distance was 5456.9 yards (DB), 4973.8 yards (WR), 4260.5 yards (RB), 4054.8 yards (LB), 4334.2 yards (TE), 3498.1 yards (DL), 3274.7 yards (OL), and 4199.2 yards (QB) respectively. Average total load was 492.8 (DB), 463.8 (WR), 393.0 (RB), 367.0 (LB), 423.9 (TE), 389.7 (DL), 381.2 (OL), and 410.8 (QB) respectively. Average explosive yardage was 472.7 (DB), 605.1 (WR), 454.5 (RB), 190.1 (LB), 320.7 (TE) 107.5 (DL), 70.6 (OL), and 191.8 (QB) respectively. Average explosive ratio was 0.847 (DB), 0.855 (WR), 1.045 (RB), 0.989 (LB), 0.985 (TE) 1.53 (DL), 1.31(OL), and 1.66 (QB) respectively. Average maximum velocity was 18.3 (DB), 17.2 (WR), 17.4 (RB), 15.7 (LB), 16.1 (TE) 13.7 (DL), 12.0 (OL), and 16.6 (QB) respectively. Average acceleration was 9.27 (DB), 8.53 (WR), 9.13 (RB), 9.78 (LB), 12.01 (TE) 21.7 (DL), 16.5 (OL), and 47.1 (QB) respectively. Average deceleration was 6.11 (DB), 4.02 (WR), 4.74 (RB), 6.11 (LB), 5.68 (TE) 8.79 (DL), 9.12 (OL), and 1.25 (QB) respectively. Average COD towards left was 6.55 (DB), 7.24 (WR), 9.09 (RB), 6.98 (LB), 9.38 (TE), 13.4 (DL), 11.3 (OL), and 8.22 (QB) respectively. Average COD towards right was 5.80 (DB), 6.45 (WR), 7.84 (RB), 5.91 (LB), 6.74 (TE) 12.5 (DL), 10.7 (OL), and 6.62 (QB) respectively. CONCLUSION: With the established healthy averages we now have a starting point for comparison of injured athletes and their rehabilitation progress. Categories most closely correlating with return to play following specific injuries is the next step. Additionally, this information may be used in injury prevention, detecting when an athlete may be overly fatigued and at great risk for injury. More data is needed to validate these numbers as well as establish criteria for healthy return to play. SAGE Publications 2019-07-29 /pmc/articles/PMC8822101/ http://dx.doi.org/10.1177/2325967119S00441 Text en © The Author(s) 2019 https://creativecommons.org/licenses/by-nc-nd/4.0/This open-access article is published and distributed under the Creative Commons Attribution - NonCommercial - No Derivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) ), which permits the noncommercial use, distribution, and reproduction of the article in any medium, provided the original author and source are credited. You may not alter, transform, or build upon this article without the permission of the Author(s). For article reuse guidelines, please visit SAGE’s website at http://www.sagepub.com/journals-permissions. |
spellingShingle | Article Moroski, Nathan M. Cain, E. Lyle Fleisig, Glenn S. Assessment Of Functional Baseline And Return To Play Criteria Using Gps Profile |
title | Assessment Of Functional Baseline And Return To Play Criteria Using Gps Profile |
title_full | Assessment Of Functional Baseline And Return To Play Criteria Using Gps Profile |
title_fullStr | Assessment Of Functional Baseline And Return To Play Criteria Using Gps Profile |
title_full_unstemmed | Assessment Of Functional Baseline And Return To Play Criteria Using Gps Profile |
title_short | Assessment Of Functional Baseline And Return To Play Criteria Using Gps Profile |
title_sort | assessment of functional baseline and return to play criteria using gps profile |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8822101/ http://dx.doi.org/10.1177/2325967119S00441 |
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