Evaluation of a two dimensional analysis method as a screening and evaluation tool for anterior cruciate ligament injury
Background: Increased knee valgus predicts the risk of anterior cruciate ligament (ACL) injury, particularly in women. Reducing injury rates thus relies on detecting and continually evaluating people with relatively large valgus motions. Objectives: To examine the potential of a two dimensional (2D)...
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| Published in | British journal of sports medicine Vol. 39; no. 6; pp. 355 - 362 |
|---|---|
| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
England
BMJ Publishing Group Ltd and British Association of Sport and Exercise Medicine
01.06.2005
BMJ Publishing Group LTD BMJ Publishing Group BMJ Group |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0306-3674 1473-0480 1473-0480 |
| DOI | 10.1136/bjsm.2005.018598 |
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| Abstract | Background: Increased knee valgus predicts the risk of anterior cruciate ligament (ACL) injury, particularly in women. Reducing injury rates thus relies on detecting and continually evaluating people with relatively large valgus motions. Objectives: To examine the potential of a two dimensional (2D) video analysis method for screening for excessive valgus. Methods: Ten female and 10 male National Collegiate Athletic Association basketball players had three dimensional (3D) knee valgus and two dimensional (2D) frontal plane knee angle quantified during side step, side jump, and shuttle run tasks. 3D valgus was quantified from external marker coordinates using standard techniques, and 2D data were obtained from both the frontal plane projections of these coordinates (2D-Mot) and manual digitisation of digital video footage (2D-Cam). A root mean square (RMS) error was calculated between 2D-Mot and 2D-Cam data to evaluate the reliability of the latter. Correlations between 2D-Cam and 3D data (intersubject and intrasubject) were also conducted, and regression slope and r2 values obtained. Results: 2D-Cam and 2D-Mot data were consistent for side step (RMS = 1.7°) and side jump (RMS = 1.5°) movements. Between subjects, 2D-Cam and 3D data correlated well for the side step (r2 = 0.58) and side jump (r2 = 0.64). Within subjects, 2D-Cam and 3D data correlated moderately for the side step (r2 = 0.25 (0.19)) and side jump (r2 = 0.36 (0.27)). Conclusions: The 2D-Cam method can be used to screen for excessive valgus in elite basketball players, particularly for movements occurring primarily in the frontal plane. This method may also be a useful training evaluation tool when large reductions in dynamic valgus motions are required. |
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| AbstractList | Background: Increased knee valgus predicts the risk of anterior cruciate ligament (ACL) injury, particularly in women. Reducing injury rates thus relies on detecting and continually evaluating people with relatively large valgus motions. Objectives: To examine the potential of a two dimensional (2D) video analysis method for screening for excessive valgus. Methods: Ten female and 10 male National Collegiate Athletic Association basketball players had three dimensional (3D) knee valgus and two dimensional (2D) frontal plane knee angle quantified during side step, side jump, and shuttle run tasks. 3D valgus was quantified from external marker coordinates using standard techniques, and 2D data were obtained from both the frontal plane projections of these coordinates (2D-Mot) and manual digitisation of digital video footage (2D-Cam). A root mean square (RMS) error was calculated between 2D-Mot and 2D-Cam data to evaluate the reliability of the latter. Correlations between 2D-Cam and 3D data (intersubject and intrasubject) were also conducted, and regression slope and r2 values obtained. Results: 2D-Cam and 2D-Mot data were consistent for side step (RMS = 1.7°) and side jump (RMS = 1.5°) movements. Between subjects, 2D-Cam and 3D data correlated well for the side step (r2 = 0.58) and side jump (r2 = 0.64). Within subjects, 2D-Cam and 3D data correlated moderately for the side step (r2 = 0.25 (0.19)) and side jump (r2 = 0.36 (0.27)). Conclusions: The 2D-Cam method can be used to screen for excessive valgus in elite basketball players, particularly for movements occurring primarily in the frontal plane. This method may also be a useful training evaluation tool when large reductions in dynamic valgus motions are required. BACKGROUND: Increased knee valgus predicts the risk of anterior cruciate ligament (ACL) injury, particularly in women. Reducing injury rates thus relies on detecting and continually evaluating people with relatively large valgus motions. OBJECTIVES: To examine the potential of a two dimensional (2D) video analysis method for screening for excessive valgus. METHODS: Ten female and 10 male National Collegiate Athletic Association basketball players had three dimensional (3D) knee valgus and two dimensional (2D) frontal plane knee angle quantified during side step, side jump, and shuttle run tasks. 3D valgus was quantified from external marker coordinates using standard techniques, and 2D data were obtained from both the frontal plane projections of these coordinates (2D-Mot) and manual digitisation of digital video footage (2D-Cam). A root mean square (RMS) error was calculated between 2D-Mot and 2D-Cam data to evaluate the reliability of the latter. Correlations between 2D-Cam and 3D data (intersubject and intrasubject) were also conducted, and regression slope and r super(2) values obtained. RESULTS: 2D-Cam and 2D-Mot data were consistent for side step (RMS = 1.7 degree ) and side jump (RMS = 1.5 degree ) movements. Between subjects, 2D-Cam and 3D data correlated well for the side step (r super(2) = 0.58) and side jump (r super(2) = 0.64). Within subjects, 2D-Cam and 3D data correlated moderately for the side step (r super(2) = 0.25 (0.19)) and side jump (r super(2) = 0.36 (0.27)). CONCLUSIONS: The 2D-Cam method can be used to screen for excessive valgus in elite basketball players, particularly for movements occurring primarily in the frontal plane. This method may also be a useful training evaluation tool when large reductions in dynamic valgus motions are required. Background: Increased knee valgus predicts the risk of anterior cruciate ligament (ACL) injury, particularly in women. Reducing injury rates thus relies on detecting and continually evaluating people with relatively large valgus motions. Objectives: To examine the potential of a two dimensional (2D) video analysis method for screening for excessive valgus. Methods: Ten female and 10 male National Collegiate Athletic Association basketball players had three dimensional (3D) knee valgus and two dimensional (2D) frontal plane knee angle quantified during side step, side jump, and shuttle run tasks. 3D valgus was quantified from external marker coordinates using standard techniques, and 2D data were obtained from both the frontal plane projections of these coordinates (2D-Mot) and manual digitisation of digital video footage (2D-Cam). A root mean square (RMS) error was calculated between 2D-Mot and 2D-Cam data to evaluate the reliability of the latter. Correlations between 2D-Cam and 3D data (intersubject and intrasubject) were also conducted, and regression slope and r 2 values obtained. Results: 2D-Cam and 2D-Mot data were consistent for side step (RMS = 1.7°) and side jump (RMS = 1.5°) movements. Between subjects, 2D-Cam and 3D data correlated well for the side step ( r 2 = 0.58) and side jump ( r 2 = 0.64). Within subjects, 2D-Cam and 3D data correlated moderately for the side step ( r 2 = 0.25 (0.19)) and side jump ( r 2 = 0.36 (0.27)). Conclusions: The 2D-Cam method can be used to screen for excessive valgus in elite basketball players, particularly for movements occurring primarily in the frontal plane. This method may also be a useful training evaluation tool when large reductions in dynamic valgus motions are required. Increased knee valgus predicts the risk of anterior cruciate ligament (ACL) injury, particularly in women. Reducing injury rates thus relies on detecting and continually evaluating people with relatively large valgus motions. To examine the potential of a two dimensional (2D) video analysis method for screening for excessive valgus. Ten female and 10 male National Collegiate Athletic Association basketball players had three dimensional (3D) knee valgus and two dimensional (2D) frontal plane knee angle quantified during side step, side jump, and shuttle run tasks. 3D valgus was quantified from external marker coordinates using standard techniques, and 2D data were obtained from both the frontal plane projections of these coordinates (2D-Mot) and manual digitization of digital video footage (2D-Cam). A root mean square (RMS) error was calculated between 2D-Mot and 2D-Cam data to evaluate the reliability of the latter. Correlations between 2D-Cam and 3D data (intersubject and intrasubject) were also conducted, and regression slope and r2 values obtained. 2D-Cam and 2D-Mot data were consistent for side step (RMS = 1.7 degrees) and side jump (RMS = 1.5 degrees) movements. Between subjects, 2D-Cam and 3D data correlated well for the side step (r2 = 0.58) and side jump (r2 = 0.64). Within subjects, 2D-Cam and 3D data correlated moderately for the side step (r2 = 0.25 (0.19)) and side jump (r2 = 0.36 (0.27)). The 2D-Cam method can be used to screen for excessive valgus in elite basketball players, particularly for movements occurring primarily in the frontal plane. This method may also be a useful training evaluation tool when large reductions in dynamic valgus motions are required. Background: Increased knee valgus predicts the risk of anterior cruciate ligament (ACL) injury, particularly in women. Reducing injury rates thus relies on detecting and continually evaluating people with relatively large valgus motions. Objectives: To examine the potential of a two dimensional (2D) video analysis method for screening for excessive valgus. Methods: Ten female and 10 male National Collegiate Athletic Association basketball players had three dimensional (3D) knee valgus and two dimensional (2D) frontal plane knee angle quantified during side step, side jump, and shuttle run tasks. 3D valgus was quantified from external marker coordinates using standard techniques, and 2D data were obtained from both the frontal plane projections of these coordinates (2D-Mot) and manual digitisation of digital video footage (2D-Cam). A root mean square (RMS) error was calculated between 2D-Mot and 2D-Cam data to evaluate the reliability of the latter. Correlations between 2D-Cam and 3D data (intersubject and intrasubject) were also conducted, and regression slope and r2 values obtained. Results: 2D-Cam and 2D-Mot data were consistent for side step (RMS = 1.7 degrees) and side jump (RMS = 1.5 degrees) movements. Between subjects, 2D-Cam and 3D data correlated well for the side step (r2 = 0.58) and side jump (r2 = 0.64). Within subjects, 2D-Cam and 3D data correlated moderately for the side step (r2 = 0.25 (0.19)) and side jump (r2 = 0.36 (0.27)). Conclusions: The 2D-Cam method can be used to screen for excessive valgus in elite basketball players, particularly for movements occurring primarily in the frontal plane. This method may also be a useful training evaluation tool when large reductions in dynamic valgus motions are required. [PUBLICATION ABSTRACT] Background: Increased knee valgus predicts the risk of anterior cruciate ligament (ACL) injury, particularly in women. Reducing injury rates thus relies on detecting and continually evaluating people with relatively large valgus motions. Objectives: To examine the potential of a two dimensional (2D) video analysis method for screening for excessive valgus. Methods: Ten female and 10 male National Collegiate Athletic Association basketball players had three dimensional (3D) knee valgus and two dimensional (2D) frontal plane knee angle quantified during side step, side jump, and shuttle run tasks. 3D valgus was quantified from external marker coordinates using standard techniques, and 2D data were obtained from both the frontal plane projections of these coordinates (2D-Mot) and manual digitisation of digital video footage (2D-Cam). A root mean square (RMS) error was calculated between 2D-Mot and 2D-Cam data to evaluate the reliability of the latter. Correlations between 2D-Cam and 3D data (intersubject and intrasubject) were also conducted, and regression slope and r 2 values obtained. Results: 2D-Cam and 2D-Mot data were consistent for side step (RMS = 1.7°) and side jump (RMS = 1.5°) movements. Between subjects, 2D-Cam and 3D data correlated well for the side step ( r 2 = 0.58) and side jump ( r 2 = 0.64). Within subjects, 2D-Cam and 3D data correlated moderately for the side step ( r 2 = 0.25 (0.19)) and side jump ( r 2 = 0.36 (0.27)). Conclusions: The 2D-Cam method can be used to screen for excessive valgus in elite basketball players, particularly for movements occurring primarily in the frontal plane. This method may also be a useful training evaluation tool when large reductions in dynamic valgus motions are required. BACKGROUND: Increased knee valgus predicts the risk of anterior cruciate ligament (ACL) injury, particularly in women. Reducing injury rates thus relies on detecting and continually evaluating people with relatively large valgus motions. OBJECTIVES: To examine the potential of a two dimensional (2D) video analysis method for screening for excessive valgus. METHODS: Ten female and 10 male National Collegiate Athletic Association basketball players had three dimensional (3D) knee valgus and two dimensional (2D) frontal plane knee angle quantified during side step, side jump, and shuttle run tasks. 3D valgus was quantified from external marker coordinates using standard techniques, and 2D data were obtained from both the frontal plane projections of these coordinates (2D-Mot) and manual digitization of digital video footage (2D-Cam). A root mean square (RMS) error was calculated between 2D-Mot and 2D-Cam data to evaluate the reliability of the latter. Correlations between 2D-Cam and 3D data (intersubject and intrasubject) were also conducted, and regression slope and r2 values obtained. RESULTS: 2D-Cam and 2D- Mot data were consistent for side step (RMS = 1.7 degrees) and side jump (RMS = 1.5 degrees) movements. Between subjects, 2D-Cam and 3D data correlated well for the side step (r2 = 0.58) and side jump (r2 = 0.64). Within subjects, 2D-Cam and 3D data correlated moderately for the side step (r2 = 0.25 (0.19)) and side jump (r2 = 0.36 (0.27)). CONCLUSIONS: The 2D-Cam method can be used to screen for excessive valgus in elite basketball players, particularly for movements occurring primarily in the frontal plane. This method may also be a useful training evaluation tool when large reductions in dynamic valgus motions are required. Increased knee valgus predicts the risk of anterior cruciate ligament (ACL) injury, particularly in women. Reducing injury rates thus relies on detecting and continually evaluating people with relatively large valgus motions.BACKGROUNDIncreased knee valgus predicts the risk of anterior cruciate ligament (ACL) injury, particularly in women. Reducing injury rates thus relies on detecting and continually evaluating people with relatively large valgus motions.To examine the potential of a two dimensional (2D) video analysis method for screening for excessive valgus.OBJECTIVESTo examine the potential of a two dimensional (2D) video analysis method for screening for excessive valgus.Ten female and 10 male National Collegiate Athletic Association basketball players had three dimensional (3D) knee valgus and two dimensional (2D) frontal plane knee angle quantified during side step, side jump, and shuttle run tasks. 3D valgus was quantified from external marker coordinates using standard techniques, and 2D data were obtained from both the frontal plane projections of these coordinates (2D-Mot) and manual digitization of digital video footage (2D-Cam). A root mean square (RMS) error was calculated between 2D-Mot and 2D-Cam data to evaluate the reliability of the latter. Correlations between 2D-Cam and 3D data (intersubject and intrasubject) were also conducted, and regression slope and r2 values obtained.METHODSTen female and 10 male National Collegiate Athletic Association basketball players had three dimensional (3D) knee valgus and two dimensional (2D) frontal plane knee angle quantified during side step, side jump, and shuttle run tasks. 3D valgus was quantified from external marker coordinates using standard techniques, and 2D data were obtained from both the frontal plane projections of these coordinates (2D-Mot) and manual digitization of digital video footage (2D-Cam). A root mean square (RMS) error was calculated between 2D-Mot and 2D-Cam data to evaluate the reliability of the latter. Correlations between 2D-Cam and 3D data (intersubject and intrasubject) were also conducted, and regression slope and r2 values obtained.2D-Cam and 2D-Mot data were consistent for side step (RMS = 1.7 degrees) and side jump (RMS = 1.5 degrees) movements. Between subjects, 2D-Cam and 3D data correlated well for the side step (r2 = 0.58) and side jump (r2 = 0.64). Within subjects, 2D-Cam and 3D data correlated moderately for the side step (r2 = 0.25 (0.19)) and side jump (r2 = 0.36 (0.27)).RESULTS2D-Cam and 2D-Mot data were consistent for side step (RMS = 1.7 degrees) and side jump (RMS = 1.5 degrees) movements. Between subjects, 2D-Cam and 3D data correlated well for the side step (r2 = 0.58) and side jump (r2 = 0.64). Within subjects, 2D-Cam and 3D data correlated moderately for the side step (r2 = 0.25 (0.19)) and side jump (r2 = 0.36 (0.27)).The 2D-Cam method can be used to screen for excessive valgus in elite basketball players, particularly for movements occurring primarily in the frontal plane. This method may also be a useful training evaluation tool when large reductions in dynamic valgus motions are required.CONCLUSIONSThe 2D-Cam method can be used to screen for excessive valgus in elite basketball players, particularly for movements occurring primarily in the frontal plane. This method may also be a useful training evaluation tool when large reductions in dynamic valgus motions are required. |
| Author | Ford, K R Hewett, T E Myer, G D van den Bogert, A J Walker, K McLean, S G |
| AuthorAffiliation | Department of Biomedical Engineering, The Cleveland Clinic Foundation, 9500 Euclid Avenue, Cleveland, OH 44195, USA. mcleans@bme.ri.ccf.org |
| AuthorAffiliation_xml | – name: Department of Biomedical Engineering, The Cleveland Clinic Foundation, 9500 Euclid Avenue, Cleveland, OH 44195, USA. mcleans@bme.ri.ccf.org |
| Author_xml | – sequence: 1 givenname: S G surname: McLean fullname: McLean, S G organization: Cincinnati Children’s Hospital, Sports Medicine Biodynamics Center, Cincinnati, OH, USA – sequence: 2 givenname: K surname: Walker fullname: Walker, K organization: Cincinnati Children’s Hospital, Sports Medicine Biodynamics Center, Cincinnati, OH, USA – sequence: 3 givenname: K R surname: Ford fullname: Ford, K R organization: Cincinnati Children’s Hospital, Sports Medicine Biodynamics Center, Cincinnati, OH, USA – sequence: 4 givenname: G D surname: Myer fullname: Myer, G D organization: Cincinnati Children’s Hospital, Sports Medicine Biodynamics Center, Cincinnati, OH, USA – sequence: 5 givenname: T E surname: Hewett fullname: Hewett, T E organization: Cincinnati Children’s Hospital, Sports Medicine Biodynamics Center, Cincinnati, OH, USA – sequence: 6 givenname: A J surname: van den Bogert fullname: van den Bogert, A J organization: Cincinnati Children’s Hospital, Sports Medicine Biodynamics Center, Cincinnati, OH, USA |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/15911607$$D View this record in MEDLINE/PubMed |
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| Notes | ark:/67375/NVC-M38XTHBN-2 Correspondence to: Dr McLean Department of Biomedical Engineering, The Cleveland Clinic Foundation, 9500 Euclid Avenue, Cleveland, OH 44195, USA; mcleans@bme.ri.ccf.org local:0390355 istex:4890010C7FA7B32CB3742218CCC8DA107A22242E href:bjsports-39-355.pdf PMID:15911607 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 ObjectType-Article-2 ObjectType-Feature-1 content type line 23 |
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| Snippet | Background: Increased knee valgus predicts the risk of anterior cruciate ligament (ACL) injury, particularly in women. Reducing injury rates thus relies on... Increased knee valgus predicts the risk of anterior cruciate ligament (ACL) injury, particularly in women. Reducing injury rates thus relies on detecting and... BACKGROUND: Increased knee valgus predicts the risk of anterior cruciate ligament (ACL) injury, particularly in women. Reducing injury rates thus relies on... Background: Increased knee valgus predicts the risk of anterior cruciate ligament (ACL) injury, particularly in women. Reducing injury rates thus relies on... |
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| SubjectTerms | ACL Adult anterior cruciate ligament Anterior Cruciate Ligament Injuries Athletic Injuries - prevention & control Basketball - injuries Biomechanical Phenomena degrees of freedom Dimensional analysis DOF Female Humans Imaging, Three-Dimensional - methods injury Kinematics Knee Knee Injuries - prevention & control Knee Joint - anatomy & histology knee valgus Ligaments Male Methods neuromuscular control Original Program Evaluation Range of Motion, Articular Research methodology RMS root mean square Sports injuries Studies three dimensional two dimensional Video Recording - methods |
| Title | Evaluation of a two dimensional analysis method as a screening and evaluation tool for anterior cruciate ligament injury |
| URI | http://bjsm.bmj.com/content/39/6/355.full https://api.istex.fr/ark:/67375/NVC-M38XTHBN-2/fulltext.pdf https://www.ncbi.nlm.nih.gov/pubmed/15911607 https://www.proquest.com/docview/1778986615 https://www.proquest.com/docview/194498351 https://www.proquest.com/docview/17343198 https://www.proquest.com/docview/67854984 https://www.proquest.com/docview/771693442 https://pubmed.ncbi.nlm.nih.gov/PMC1725240 |
| Volume | 39 |
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