In recent years, the functional movement screen (FMS) and FMS training have attracted attention as a means of preventing injury, but no studies have examined the effect of such training in ...high-school baseball players. The aim of this study was to clarify the effect of FMS training on FMS score, physical function and baseball performance in high-school baseball players.
Subjects in this randomized controlled clinical trial were high-school male baseball players assigned to either an FMS training group (intervention group) or a control group. The intervention group performed FMS training 4 times per week for 12 weeks. FMS ability, physical function, and baseball performance were measured prior to the intervention, 8, 12, and 24 weeks after the intervention in the subjects' school environment.
A total of 71 baseball players aged 15 to 17 years were recruited and assigned to either an intervention group (n = 37) or control group (n = 34). There was no significant difference in the characteristics of participants between the 2 groups. Most FMS scores improved to 12 weeks after continued training. In the intervention group compared with the control group, deep squat, hurdle step, inline lunge, active straight leg raise, trunk stability push-up and rotary stability FMS score, total FMS score and eyes closed single leg stance time significantly increased after 8 weeks of training. While hurdle step, inline lunge, active straight leg raise, trunk stability push-up, total FMS score, and eyes closed single leg stance time significantly increased, pitching ball speed significantly decreased at the end of the 12 week training period. Eyes closed single leg stance time and feeling of fatigue significantly improved 12 weeks after training. The number of subjects who scored less than 14 for the total FMS score in the intervention group compared with control group were significantly less after 8 and 12 weeks of FMS training.
FMS training for 8 weeks contributes to improving FMS scores for high-school baseball players, but FMS scores go down if FMS training is not continued.
University Hospital Medical Information Network Center, Tokyo, Japan: UMIN000027553. Registered on May 30, 2017.
Le rugby est devenu au fil des ans un des sports les plus populaires ; en témoigne l’engouement autour de la dernière Coupe du monde en France. Il s’agit cependant d’un sport qui demande des efforts ...physiques intenses et peut occasionner des blessures. Repérer ces blessures chez le joueur amateur nécessite un outil de dépistage. Ceci peut être réalisé à l’aide du Functional Movement Screen (FMS). L’objectif principal de cette étude était de déterminer la reproductibilité intra- et inter-évaluateur de ce test chez les joueurs de rugby amateurs. L’objectif secondaire de l’étude était d’évaluer les aptitudes du test comme outil prédictif de dépistage des éventuelles blessures pendant une saison sportive.
Des rugbymen amateurs (n=61) ont réalisé les sept mouvements nécessaires à l’établissement du score du Functional Movement Screen sous la surveillance de deux évaluateurs : la comparaison des scores servait à évaluer la reproductibilité inter-évaluateur. Quarante d’entre eux ont repassé le test une semaine plus tard pour évaluer la reproductibilité intra-évaluateur, en comparant les scores de chaque joueur à différents moments par le même évaluateur. Des coefficients intraclasses ont été utilisés pour déterminer les reproductibilités. Les blessures de chaque joueur étaient comptabilisées et mises en relation avec les scores du test via un coefficient de Spearman.
La reproductibilité inter-évaluateur du score composite du test était de bonne qualité ; la reproductibilité intra-évaluateur était de bonne qualité. Du fait d’une trop faible survenue d’évènements « blessures », il n’a pas été possible d’évaluer le test comme outil de dépistage des blessures.
Le Functional Movement Screen est un instrument reproductible, facile d’utilisation. Il ne peut cependant pas être considéré actuellement comme un instrument de dépistage des blessures dans le rugby amateur.
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Over the years, rugby has become one of the most popular sports, as evidenced by the excitement surrounding the last World Cup in France. However, it is a sport requiring intense physical effort and can cause injuries. Identifying these injuries in amateur players requires a screening tool. This will be the Functional Movement Screen. The main objective was to determine the intra- and inter-rater reproducibility of the test in amateur rugby players. The study's secondary objective was to evaluate the capabilities of the test as a predictive tool for screening possible injuries during a sports season.
Amateur rugby players (n=61) performed the seven movements necessary to establish the test score under supervision of two evaluators: the comparison of scores was used to assess inter-rater reproducibility. Fourty of them took the test again a week later to assess intra-rater reproducibility, by comparing each player's scores at different times by the same evaluator. Intraclass coefficients were used to determine reproducibility. The injuries of each player were counted and linked to the test scores via Spearman coefficient.
The inter-rater reproducibility of the test composite score was good; the intra-rater reproducibility of the test composite score was good. With a low occurrence of “injury” events, evaluating the test in our study as an injury screening tool was not possible.
The Functional Movement Screen is a reproducible, easy-to-use instrument. However, it cannot currently be seen as an injury screening instrument in amateur rugby.
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Objective: The present study aimed to compare the Functional Movement Screen (FMS) scores between athlete and non-athlete female students. Methods: Participants were 30 athlete female students ...(Mean±SD age, 23.36±3.10 years; Mean±SD height, 163.45±5.06 cm; Mean±SD weight, 57.40±6.43 kg) and 30 non-athlete female students (Mean±SD age, 25.00±2.36 years; Mean±SD height, 162.6±3.72; Mean±SD weight, 58.76±9.29 kg). They underwent FMS to assess their movement patterns. Mann–Whitney U test was used to compare the mean FMS scores between athletes and non-athletes. Data analysis was performed in SPSS v. 22 software at a significance level of P≥0.05. Results: The Mann–Whitney U test results showed a significant difference between the total mean FMS scores of female athletes and non-athletes (P=0.001). Considering a cut-off point of 14, Results revealed that 66% of athletes 40% of non-athletes had a FMS score <14, while 93.34% of athletes and 60% of non-athletes had a FMS score >14. Conclusion: FMS can help identify the difference in movement patterns between female athletes and non-athletes. Higher FMS scores of female athletes indicate that non-athletes have poor movement patterns which suggest that they are more likely to be injured if they engage in sports activities.
The functional movement screen is developed to examine individuals' movement patterns through 7 functional tasks. The purpose of this study was to identify the internal consistency and factor ...structure of the 7 tasks of the functional movement screen in elite athletes; 290 elite athletes from a variety of Chinese national teams were assessed using the functional movement screen. Cronbach's alpha was calculated for the scores of the 7 tasks. Exploratory factor analysis was performed to explore the factor structure of the functional movement screen. The mean and standard deviation of the sum score were 15.2 ± 3.0. A low Cronbach's alpha (0.58) was found for the scores of the 7 tasks. Exploratory factor analysis extracted 2 factors with eigenvalues greater than 1, and these 2 factors explained 47.3% of the total variance. The first factor had a high loading on the rotatory stability (loading = 0.99) and low loadings on the other 6 tasks (loading range: 0.04-0.34). The second factor had high loadings on the deep squat, hurdle step and inline lunge (loading range: 0.46-0.61) and low loadings on the other 3 tasks (loading range: 0.12-0.32). The 7 tasks of the functional movement screen had low internal consistency and were not indicators of a single factor. Evidence for unidimensionality was not found for the functional movement screen in elite athletes. More attention should be paid to the score of each task rather than the sum score when we interpret the functional movement screen scores.
This study aims to analyse the effects of functional training on muscle strength, jumping, and functional movement screen in wushu athletes. Methods: This study followed the guidelines of the ...Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). A systematic search of electronic databases was also conducted, including EBSCOhost, Scopus, PubMed, Web of Science, CNKI, Google Scholar, and Wanfang. The Physiotherapy Evidence Database (PEDro) scale was an effective indicator to evaluate the quality of studies included in the systematic review. Results: This systematic review included 474 participants aged 8–24 years old. The intervention period for most studies was 12 weeks. Among the included studies, 6 focused on muscle strength, 4 on jumping performance, and 11 on functional movement screen. Conclusion: These articles have been analysed, and the positive impact of functional training interventions on muscle strength, jumping, and functional movement screen of wushu athletes has been verified.
Although the functional movement screen (FMS) has been widely applied for screening athletes, no previous study has used FMS scores to examine the association between distinct training seasons in ...high school baseball players. The aims of this study were to ascertain the functional movement screen (FMS) scores differences between the preparative period (PPP) and the competitive period (CPP) among high school baseball players and further determine whether FMS can be used as a tool to predict injuries during two major periods.
Fifty-five male high school baseball players (age 15.3 ± 1.7 years; height 1.7 ± 0.8 m; weight 64.6 ± 11.5 kg) volunteered. Athletic injuries were reported through a self-report questionnaire. Players performed the FMS during the PPP and the CPP. A receiver operator characteristic (ROC) curve to calculate a cutoff total composite score ≤ 14 for the relationship between the FMS score and injury. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and an area under the curve (AUC) were calculated.
FMS individual task score and total composite score were significantly lower in the CPP than in the PPP. However, a cutoff total composite score ≤14 for risk of injury, determined through a ROC curve, represented a low sensitivity of 58%, NPV of 66%, an AUC of 69%, specificity of 79%, and PPV of 71%.
Although the low sensitivity and NPV and AUC scores indicated that the FMS does not accurately predict the risk of injury, the FMS individual task and total composite scores differed significantly between the PPP and CPP. Therefore, FMS could be used as a tool to identify physical deficiencies between distinct training seasons; however, utilizing the FMS as a screening tool for injury prediction in particular during the CPP in this population would not be recommended.
•Utilizing the FMS for injury prediction in high school baseball players would not be recommended.•FMS individual task and total composite scores differed significantly between distinct training seasons.•FMS could be used as a tool to identify physical deficiencies in the distinct training seasons.
Purpose This study assessed the exercise capacity of healthy adults while performing the inline lunge exercise by using Functional Movement Screen (FMS). Compared the difference in muscle activity of ...the quadriceps according to the exercise capacity. Participants and Methods Thirty two healthy participants (12 males, 20 females) participated in this study. The surface electromyography (sEMG) was used to measure the electrical activities for the vastus medialis (VM), rectus femoris (RF), vastus lateralis (VL) of quadriceps. Results Both groups had significant difference when sitting up and getting up during the inline lunge. In scores 3 group, vastus medialis showed higher muscle activity than vastus lateralis. On contrary, in scores 2 group, vastus lateralis had higher muscle activity than vastus medialis. Conclusion Therefore, this study suggests that inline lunge can help to strengthen the quadriceps effectively by showing the difference of quadriceps activity according to exercise capacity.
The study objective is to evaluate the possibility of using screening methods for determining the effectiveness of health and fitness activities of students in higher education institutions.
...Materials and methods. The participants in the experiment were 37 first-year students (17 boys and 20 girls) of the School of History of H. S. Skovoroda Kharkiv National Pedagogical University. The experiment lasted during the fall semester. Using the Framingham method for analyzing weekly timing, the study conducted a survey among the students on their level of motor activity and performed a functional movement screen testing. To tentatively evaluate the cause and effect relationship between the level of motor activity and the occurrence of a pathological movement pattern, the study used the Spearman’s rank correlation coefficient. The characteristics between the groups were analyzed by using the Mann-Whitney test for comparing the distribution of ordinal variables.
Results. The correlation analysis showed that the first-year students’ motor activity was positively related to the results of functional movement screening (R=+0.69, p< 0.05). At the same time, the students (EG1) who mainly had a high level of physical activity at physical education classes showed low values of functional movement evaluation, compared to the students (EG2) participating in extra-curricular physical activity. In EG1, the overall screening score was 10.3±0.7, in EG2 — 14.2±0.9 (p<0.05).
Conclusions. The students with insufficient weekly motor activity had risk values of the test (10.3±0.7), which requires further analysis of the causes of a pathological movement pattern. The study results have confirmed the existence of the relationship between motor activity indicators and functional movement evaluation (R=+0.69, p<0.05). This provides a way to use the screening method of determining motor competence for the effectiveness evaluation of health and fitness programs, but further research is needed.
Evidence that the test is valid is lacking.2 3 A second approach to assess readiness to play is to use statistical models, informed by guidelines of football governing bodies that include a variety ...of potential risk factors.4 5 Existing models lack precision or clinical usefulness in predicting events such as injury. Subsequent injury surveillance was conducted by the team physiotherapist and injuries recorded in the team database (in accordance with the consensus statement for data collection and injury reporting).4 In study 3, I developed an injury model based on a variety of risk factors identified in the literature and recommended by football governing bodies (including previous injury, acute to chronic workload ratio, fitness measures and other factors related to participation in football). ...work is needed to identify appropriate predictor variables and modelling methods that can be used to model injury risk and help inform clinical decision-making.
FMS stands for functional movement screen, which is a simple and effective method to evaluate athletes’ basic sports ability. This paper proposed a real-time FMS action classification method. ...Correspondingly, a video set was constructed with two different perspectives including 8 testers, 13 independent testing processes and 360574 images. Moreover, a normalization algorithm and a result correction algorithm is proposed to improve the performance of the models and make the result sequence more continuously. Furthermore, it has the vital significance to FMS action evaluation. Finally, this paper analyzed the effectiveness of different models and compared their performance from the aspects of accuracy, continuity, running speed, etc. The experimental results show that our method can achieve 96.7% precision score and 94.7% recall score on the test set. And the average running speed of the system is over 30 FPS. All related data, benchmarks and codes will be uploaded on https://github.com/bobogo/FMS-evaluation-system.
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•The basic architecture and test environment of FMS motion evaluation are designed.•An appropriate and efficient method to classify 14 FMS actions is presented.•A new FMS dataset with two orthogonal perspectives and wide-ranging cases is built.•Benchmark for FMS imagery are given in terms of accuracy, continuity and speed.
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