scholarly journals Use of a Functional Movement Screening Tool to Determine Injury Risk in Collegiate Acrobatics and Tumbling Athletes

2016 ◽  
Author(s):  
Sara E. Spencer
Keyword(s):  
Injury Risk ◽  
Screening Tool ◽  
Functional Movement ◽  
Movement Screening ◽  
Functional Movement Screening

scholarly journals Effect of Fatigue on Functional Movement Screening Performance in Dancers

2018 ◽  
Vol 33 (3) ◽  
pp. 213-219 ◽  
Author(s):  
Ross Armstrong ◽  
Christopher M Brogden ◽  
Debbie Milner ◽  
Debbie Norris ◽  
Matt Greig
Keyword(s):  
Injury Risk ◽  
Perceived Exertion ◽  
Neuromuscular Control ◽  
Functional Movement ◽  
Screening Performance ◽  
Movement Screening ◽  
And Performance ◽  
High Level ◽  
Deep Squat ◽  
Functional Movement Screening

OBJECTIVE: Dance is associated with a high risk of injury, with fatigue identified as a contributing factor. Functional movement screening (FMS) has been used to identify alterations in normal movement which may contribute to injury risk, though this test is not normally performed in a fatigued state. The aim of this study was to determine whether fatigue induced by the dance aerobic fitness test (DAFT) results in changes in FMS scores with implications for performance and injury risk. METHODS: Forty-one university dancers completed the FMS before and immediately after completion of the DAFT. Rate of perceived exertion and heart rate were quantified as measures of fatigue. RESULTS: Post-DAFT, the mean FMS composite score (15.39±1.86) was significantly less (p≤0.01) than the pre-exercise score (16.83±1.83). Element-specific analysis revealed that the deep squat, non-dominant lunge, and dominant inline lunge scores were all significantly impaired post-DAFT (all p≤0.01). CONCLUSION: The identification of changes in quality of movement in a fatigued state suggests that movement screening should also be performed post-exercise to enhance screening for injury risk. The influence of dance-specific fatigue was FMS element-specific. Specifically, the deep squat and inline lunge were most susceptible to fatigue, with implications for injury risk and performance and reflective of the high level of neuromuscular control required.

scholarly journals Asymmetry during Functional Movement Screening and injury risk in junior football players: A replication study

2018 ◽  
Vol 28 (3) ◽  
pp. 1281-1287 ◽  
Author(s):  
S. Chalmers ◽  
T. A. Debenedictis ◽  
A. Zacharia ◽  
S. Townsley ◽  
C. Gleeson ◽  
...  
Keyword(s):  
Injury Risk ◽  
Replication Study ◽  
Football Players ◽  
Functional Movement ◽  
Movement Screening ◽  
Functional Movement Screening

scholarly journals Big Data and Deep Learning Model for FMS Score Prediction of Aerobics Athletes

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Wenying Xiong ◽  
Dongqin Huang ◽  
Wei Xu
Keyword(s):  
Big Data ◽  
Deep Learning ◽  
Injury Risk ◽  
Risk Model ◽  
Sports Injuries ◽  
Sports Injury ◽  
Positive Role ◽  
Functional Movement ◽  
Movement Screening ◽  
Functional Movement Screening

In recent years, competitive aerobics has developed rapidly in my country, and the corresponding sports injury risks have gradually increased. A number of studies have shown that due to the characteristics of aerobics itself, difficult movement requirements, fast-paced music accompaniment and coherent coordinated movements, athletes will suffer sports injuries if they are not paying attention. Therefore, discovering the causes of athletes’ injuries in time and preventing them in time is crucial for improving athletes’ skill level and prolonging sports life. Through the functional movement screening (FMS) test, understanding young aerobics athletes’ insufficiency in trunk stability, joint flexibility, muscle extension, and core strength can further help athletes reduce the risk of sports injuries. Therefore, this article proposes a novel sports injury risk model based on big data technology and deep learning, which can effectively predict the risk of sports injury and can play a positive role in improving the quality of athletes’ movements and prolonging their sports life.

Functional Movement Screening and injury risk in elite adolescent rugby league players

2019 ◽  
Vol 14 (4) ◽  
pp. 498-506
Author(s):  
Cameron S Dyer ◽  
Robin Callister ◽  
Colin E Sanctuary ◽  
Suzanne J Snodgrass
Keyword(s):  
Injury Risk ◽  
Rugby League ◽  
Injury Incidence ◽  
Functional Movement Screen ◽  
Functional Movement ◽  
Incidence Data ◽  
Movement Screening ◽  
The Mean ◽  
Functional Movement Screening ◽  
And Training

Research is limited as to whether Functional Movement Screen scores relate to non-contact injury risk in rugby league players. This cohort study investigates whether the Functional Movement Screen score predicts non-contact injuries in elite adolescent rugby league players. Australian adolescent rugby league players ( n = 52; mean age 16.0 ± 1.0 years) from one club participated in this study. Functional Movement Screen scores, height, and mass were collected at the beginning of the preseason. Training, match exposure, and injury incidence data (non-contact match and training injuries with three levels of severity) were recorded for each individual athlete throughout the season. Linear and logistic regression analyses were conducted to investigate the association between Functional Movement Screen score (continuous score, ≤ 14 or > 14, and three subscores) and injury risk, whilst controlling for exposure time. The mean Functional Movement Screen score for the sample was 13.4 (95% CI: 11.0–14.0). A total of 72 non-contact injuries were recorded (incidence rate: 18.7 per 1000 exposure hours; 95% CI: 11.6–24.8). There were no statistically significant associations between non-contact injury and Functional Movement Screen score for any of the analyses conducted. Our results suggest that the Functional Movement Screen does not reflect non-contact injury risk in elite adolescent rugby league players. Further research should investigate whether a more sport-specific movement screen in the preseason can more effectively predict injury risk in this population.

scholarly journals Dynamic Movement Assessment and Functional Movement Screening for injury prediction: a systematic review

2018 ◽  
Vol 25 (3) ◽  
pp. 352-361
Author(s):  
Priscila dos Santos Bunn ◽  
Elirez Bezerra da Silva
Keyword(s):  
Systematic Review ◽  
Injury Risk ◽  
Physical Activities ◽  
Musculoskeletal Injuries ◽  
Functional Movement ◽  
Injury Prediction ◽  
Dynamic Movement ◽  
Movement Screening ◽  
Movement Assessment ◽  
Functional Movement Screening

ABSTRACT Dynamic Movement AssessmentTM (DMATM) and Functional Movement ScreeningTM (FMSTM) are tools to predict the risk of musculoskeletal injuries in individuals who practice physical activities. This systematic review aimed to evaluate the association of DMATM and FMSTM with the risk of musculoskeletal injuries, in different physical activities, categorizing by analysis. A research without language or time filters was carried out in November 2016 in MEDLINE, Google Scholar, SciELO, SCOPUS, SPORTDiscus, CINAHL and BVS databases using the keywords: “injury prediction”, “injury risk”, “sensitivity”, “specificity”, “functional movement screening”, and “dynamic movement assessment”. Prospective studies that analyzed the association between DMATM and FMSTM with the risk of musculoskeletal injuries in physical activities were included. The data extracted from the studies were: participant’s profile, sample size, injury’s classification criteria, follow-up time, and the results presented, subdivided by the type of statistical analysis. The risk of bias was performed with Newcastle-Ottawa Scale for cohort studies. No study with DMATM was found. A total of 20 FMSTM studies analyzing one or more of the following indicators were included: diagnostic accuracy (PPV, NPV and AUC), odds ratios (OR) or relative risk (RR). FMSTM showed a sensitivity=12 to 99%; specificity=38 to 97%; PPV=25 to 91%; NPV=28 to 85%; AUC=0.42 to 0.68; OR=0.53 to 54.5; and RR=0.16-5.44. The FMSTM has proven to be a predictor of musculoskeletal injuries. However, due to methodological limitations, its indiscriminate usage should be avoided.

scholarly journals Functional Movement Screening: An Early Detection of The Student Injury Risk in Sport Class

2020 ◽  
Vol 5 (2) ◽  
Author(s):  
Muhamad Syafei ◽  
Didik Rilastiyo Budi ◽  
Arfin Deri Listiandi ◽  
Rifqi Festiawan ◽  
Kusnadar Kusnandar ◽  
...  
Keyword(s):  
Physical Education ◽  
Injury Risk ◽  
Test Method ◽  
Physical Education Class ◽  
Functional Movement ◽  
Physical Test ◽  
Education Class ◽  
Ex Post ◽  
Movement Screening ◽  
Functional Movement Screening

Physical Education class is one of the solutions taken by regional schools to improve achievements in sports. The process of recruiting physical education class students has mostly conducted by using  the talent scouting test method which consists of physical test and skill test. However, the implementation of sport injury detection test using Functional Movement Screening (FMS) is still insignificant. The purpose of this study was to identify the student risk of injury in physical education class by using the FMS test. The research was an ex-post-facto method. The research samples were 32  students of class VIII in the physical education class at SMPN 1 Baturaden (20 males and 12 females) aged 14 years in average. The research instrument used was the Functional Movement Screening (FMS) test with the validity and reliability of 0.81. Data processing and analysis employed the Benchmark Reference (PAN) with the help of Ms. Excel. The results showed that 56.25% of physical education class students at SMPN 1 Baturaden were identified at risk of sports injuries. The results also showed an imbalance of strength between the right and left body muscles. The study  concludes that the use of Functional Movement Screening (FMS) test is important to minimize the high likelihood of injury of the students in physical education class.

THE FUNCTIONAL MOVEMENT SCREENING TOOL DOES NOT PREDICT INJURY IN FOOTBALL

2015 ◽  
Vol 1 (2) ◽  
pp. 41 ◽  
Author(s):  
Christopher Rusling ◽  
Kimberley Edwards ◽  
Archan Bhattacharya ◽  
Adam Reed ◽  
Stuart Irwin ◽  
...  
Keyword(s):  
Screening Tool ◽  
Functional Movement ◽  
Movement Screening ◽  
Functional Movement Screening

Efficacy of Functional Movement Screening for Predicting Injuries in Coast Guard Cadets

2015 ◽  
Vol 29 (5) ◽  
pp. 1157-1162 ◽  
Author(s):  
Joseph J. Knapik ◽  
Ludimila M. Cosio-Lima ◽  
Katy L. Reynolds ◽  
Richard S. Shumway
Keyword(s):  
Coast Guard ◽  
Functional Movement ◽  
Movement Screening ◽  
Functional Movement Screening

scholarly journals THE RELATION BETWEEN ESTIMATED MOTOR SKILLS WITH FUNCTIONAL MOVEMENT SCREENING AND PERFORMANCE OF GYMNASTIC ELEMENTS ON THE FLOOR ROUTINE AND THE VAULT

2019 ◽  
Vol 13 (2) ◽  
Author(s):  
Saša Jovanović ◽  
Adriana Ljubojević ◽  
Violeta Novaković
Keyword(s):  
Motor Skills ◽  
Statistical Significance ◽  
Screening Method ◽  
Predictor Variable ◽  
General Information ◽  
Integral Model ◽  
Functional Movement ◽  
Significance Level ◽  
Movement Screening ◽  
Functional Movement Screening

The aim of this research was to verify the FMS (Functional Movement Screening) method as apredictor of success in performing gymnastic elements on the floor routine and vault, on aselected sample composed of 36 male subjects aged 20 - 22 years, students of Faculty ofPhysical Education and Sport, University of Banja Luka. A battery of 11 motor skills tests wasassessed: 7 at floor routine (side-to-side and front-to-back cartwheel, roundoff, front and backhandspring, forward and backward flip) and 4 on vault (squat through on the vault and straddlevault with pre-flight, front handspring on vault, roundoff vault) together with FMS resultsall results received normal distribution and a relatively low average FMS value(14.313), which according to many authors is near the limit of the risk of injury (14). The overallresults of the correlation analysis indicated statistically significant relationship between FMSand variables PRENAZ (0.049) and SALNAZ (0.038) at significance level of0.05, while the applied regression analysis gave general information on the prediction modelthat showed statistical significance of 0.03 with the predictor variable FMS at the level of significance0.05. Observing the values of the determination coefficients R2, it was establishedthat the FMS method can predict the performance of the selected gymnastic elements on thefloor routine and the vault as an integral model, explaining about 96% of the common variabilitywith a criterion, representing a significant statistical value.

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