Functional Movement Screen™ (Fms™) Scores Do Not Predict Overall or Lower Extremity Injury Risk in Collegiate Dancers

Coogan, Sarah M.; Schock, Catherine S.; Hansen-Honeycutt, Jena; Caswell, Shane V.; Cortés, Nelson; Ambegaonkar, Jatin P.

doi:10.26603/ijspt20201029

Cited by 4 publications

(3 citation statements)

References 30 publications

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“…Convolutional neural network (CNN) is a multilayer neural network. Figure 3 shows the basic architecture of the convolutional neural network [ 22 ]. Among them, the application of convolutional neural networks is quite extensive, and it is widely used in image recognition, object recognition, behavior cognition, pose estimation, and neural style transfer in computer vision.…”

Section: Methods Of Automatic Arrangement Of Sports Dance Based On De...mentioning

confidence: 99%

Automatic Arrangement of Sports Dance Movement Based on Deep Learning

Feng

Zhao

Zhang

2022

Computational Intelligence and Neuroscience

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Sports dance is a new form of sports that integrates sports, dance, music, and other elements. The core content of “dance” is an important carrier for athletes to display their body art. This article aims to study the automatic arrangement of sports dance based on deep learning. This article first introduces the development process of deep learning. As the latest research direction developed from artificial neural network technology in machine learning, deep learning has attracted widespread attention from the society. And then proposing a shallow regression model based on deep learning, a convolutional neural network based on deep learning, and an offline sorting regression model, given the general process of deep learning, then, based on the clustering algorithm, the deep learning was researched, and the sport dance movement arrangement was analyzed based on the deep learning. The experimental results of this article show that deep learning can effectively enhance the artistic ability of automatic choreography in sports dance and increase the accuracy of dance movements by 80%. At the same time, on the basis of deep learning, the practical ability is strengthened on the basis of consolidating theory, to further improve one’s own business ability and educational technology level, actively absorb advanced teaching methods, and earnestly delve into reasonable teaching methods. It is also used in curriculum training practice to actively gain insight into new development trends in educational methods and skills, to enhance the artistic creativity of students’ arrangements.

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Section: Methods Of Automatic Arrangement Of Sports Dance Based On De...mentioning

confidence: 99%

Automatic Arrangement of Sports Dance Movement Based on Deep Learning

Feng

Zhao

Zhang

2022

Computational Intelligence and Neuroscience

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“…Functional Movement Screening (FMS) identifies potential risk factors associated with injury in people who exercise or participate in sporting activities (Coogan et al, 2020). The test in FMS includes seven movements, namely inline lunge, hurdle step, deep squat, shoulder mobility, active straight leg raise, trunk stability push-up, and rotary stability (Cook et al, 2014).…”

Section: Frequency Distribution Of Flexibilitymentioning

confidence: 99%

Injury risk potential and flexibility level: An analysis of amateur team sport athletes

Herstiani-S,

Anam

2024

j. Sport Area

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Background Problems: Sports injuries are a severe problem that can affect an athlete's career, including those active in team sports such as basketball, volleyball, and futsal. Research Objectives: This study aims to analyse the potential risk of injury and the level of flexibility of amateur athletes at Universitas Negeri Semarang. Methods: This research is a quantitative descriptive study using the sampling technique, namely purposive sampling, to obtain a total sample of 90 athletes. Instruments to measure the potential risk of injury use the functional movement screen (FMS) and the level of flexibility using the sit-and-reach test. The data analysis techniques use descriptive statistical analysis. Findings and Results: The results of the FMS analysis showed that most male and female amateur athletes had a low level of injury risk. Flexibility measurements show that most male and female amateur athletes have good flexibility. This study contributes to understanding the potential risk of injury and the level of flexibility in amateur team sport athletes. Conclusion: The findings can assist coaches and teams in designing more effective training programmes to improve athletes' physical health and performance. Further research is recommended to analyse other physical condition component variables, as well as research subjects from different age groups. In addition, it is also recommended that more research samples from various levels of athletes be examined.

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“…The reason for the increase in injuries is deemed a significant physical exertion in dancing. Most dancers' injuries are related to the lower extremity (LE) and are chronic [61]. It has been proposed to use the Functional Movement Screen (TM) (FMS(TM)) as a screening tool to determine the risk of injury.…”

Section: Injury Prevention In Sports Dancing and Their Rehabilitation...mentioning

confidence: 99%

Priority scientific areas in sports dances research: the analysis of the scientific resources of Web of Science Core Collection

Podrihalo

Xiaohong

Mulyk

et al. 2022

PES

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Background and Study Aim. The increase in the popularity of sports dances recently has been confirmed. Dancing combines sports and aesthetic components. Dances are used for sports, recreational and rehabilitation purposes. The study aim is an analytical analysis of publications devoted to sports dances and the determination of priority scientific areas in this field. Material and Methods. The bibliometric database Web of Science Core Collection (WoS) is analyzed. For the primary analysis, 618 sources were selected which met the search criteria for 2018–2022. We used bibliometric methods for processing the information received in the context of sports dances for 173 sources. The VOSviewer 1.6.18 program was used: keyword analysis method and direct citation analysis with the construction of bibliometric maps, visualization of cluster density, weights – citations. Results. The constructed bibliometric maps made it possible to identify the leading thematic areas of research, current areas of research in this field. They can be divided into sports, recreational, medical and rehabilitation areas. The sports context is aimed at studying the performance of technical elements, the development of the physical qualities of athletes, the assessment of physical fitness, the dynamics of the morphofunctional state. Psychophysiological studies are aimed at analyzing balance and equilibrium. Publications of a recreational orientation study the health-improving use of dances, their impact on health. The medical and rehabilitation direction explores the features of sports injuries in dancing, injury prevention and the possibility of using dances in the complex rehabilitation. The use of the VOSviewer program, version 1.6.18, made it possible to conduct a comprehensive analysis of the problem, to determine the priority scientific directions in this area. Conclusions. The conducted bibliometric analysis of publications confirms the relevance of the problem of sports dances. A constant research interest in this problem has been determined. Research in this area has a pronounced sports and medical focus. Bibliometric analysis of publications allows identification the three following areas: sports, recreation and rehabilitation. Dancing is being explored as a sport, a form of physical activity, and a form of rehabilitation. A fairly high level of sports injuries has led to interest in the analysis of the prevalence and prevention of injuries. Its characteristic feature is the intersection of these directions. The study of athletes’ state confirmed the lack of works devoted to a comprehensive study of athletes, predicting success and skill growth. There are not enough works studying the physical state of sports dancers. There are practically no studies aimed at studying the psychophysiological state. These types of studies should be assessed as relevant.

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Functional Movement Screen™ (Fms™) Scores Do Not Predict Overall or Lower Extremity Injury Risk in Collegiate Dancers

Cited by 4 publications

References 30 publications

Automatic Arrangement of Sports Dance Movement Based on Deep Learning

Automatic Arrangement of Sports Dance Movement Based on Deep Learning

Injury risk potential and flexibility level: An analysis of amateur team sport athletes

Priority scientific areas in sports dances research: the analysis of the scientific resources of Web of Science Core Collection

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