Beach volleyball athlete training trends of Russian-language scientific resources: a systematic review

Єрмаков, Сергій; Yermakova, Tetiana; Wnorowski, Krzysztof; Bensbaa, Abdelkrim

doi:10.15561/20755279.2021.0508

Cited by 6 publications

(4 citation statements)

References 37 publications

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“…There have been numerous theoretical and empirical studies on the current state of physical fitness training research, difficulties that exist, and potential directions for growth by domestic scholars in recent years. Studies on physical training theory and practice in the United States and overseas tend to focus on the microcosmic level of understanding and quantitative analysis, instead of the macrocosmic level [1][2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Simulation Analysis of Physical Fitness Training via Deep Learning Algorithm

Qing-dong

2022

Wireless Communications and Mobile Computing

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Physical fitness is defined as a person's capacity to perform at a high level in terms of their strength, speed, endurance, coordination, flexibility, agility, and other athletic attributes. The morphological and functional aspects of the human body are intimately linked when it comes to determining one's level of physical fitness. It is possible to categorize physical fitness into two types: healthy physical fitness and competitive physical fitness, depending on the performance and role it plays in various groups of individuals. Competitive physical fitness is built on the foundation of healthy physical fitness, which is the ability of the organ systems to work properly for a particular set of people. Healthful physical fitness is a prerequisite for the future growth of competitive competition. The simulation study of physical fitness training is an important topic, regardless of whether the goal is to achieve healthy physical fitness or competitive physical fitness. This work combines it with deep learning algorithms to propose a strategy MPRN-ATT-LSTM for physical training simulation analysis. First, this work proposes the idea of a hybrid model, which uses a residual network structure (MPRN) with a pooling layer to learn features from time series to reduce the dimension. Then, the extracted feature vector is sent to the LSTM model for further feature extraction. Considering that the LSTM model has high requirements on sequence of input sequence, when input sequence is changed or unreasonable, it may lead to inaccurate feature extraction and affect the classification results. This work solves this problem by adding a self-attention mechanism, which can better focus on information important for classification and give higher weights. Finally, a large number of experiments are carried out in this work to verify the superiority of this method for simulation analysis of physical training.

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Section: Introductionmentioning

confidence: 99%

Simulation Analysis of Physical Fitness Training via Deep Learning Algorithm

Qing-dong

2022

Wireless Communications and Mobile Computing

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“…This article selects four main items in the McGill test: lumbar flexion, extension, right bridge, and left bridge. 4 This paper examines athletes' core strength test results before and after the test.…”

Section: Test Schemementioning

confidence: 99%

Abdominal Core Strength Training in Female Volleyball Players

Sun

2023

Rev Bras Med Esporte

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Introduction: The performance of female volleyball players depends heavily on the stability of the abdominal center. This stabilization system provides the players with a stable performance during exercises. Abdominal core strength training can also improve the efficiency and accuracy of body movements, although its studies in volleyball players lack evidence. Objective: Examine the effect of abdominal core strength training on physical fitness in female volleyball players. Methods: Eighteen female volleyball players were randomly selected and divided into two groups. The experimental group performed abdominal core strength exercises. The control group practiced regular physical exercises. The experiment lasted 12 weeks. The article addressed eight primary test items. Among them, the waist extension test and the adapted bridge test were the main indicators of the center of gravity stability. The experiment's results were analyzed by comparing the data before and after the intervention by mathematical and statistical methods. Results: The experimental group improved significantly in all aspects after 12 weeks of abdominal core strength training (P<0.05). The experimental group's results were significantly improved (P<0.05). Conclusion: Abdominal core strength training promotes the development of stability, coordination, and agility in young female volleyball players. The exercises explored to strengthen the abdominal center are indicated for women's volleyball teams. Level of evidence II; Therapeutic studies - investigation of treatment outcomes.

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“…Although the presentation of bibliometric analysis research through visualised maps has been quite widespread in recent years, it is observed that such research is limited to certain areas. In this regard, some bibliometric studies in the field of physical education and sports were detected by scanning the "Web of Science (WoS)" database Contreras-Barraza et al, 2021;Chiu et al, 2021;Iermakov et al, 2021;Baier-Fuentes et al, 2020;Tomanek & Lis, 2020;Jiménez-García et al, 2020;Büyükbaykal & İli, 2020;Gholampour et al, 2019;Huertas González-Serrano et al, 2020;Lis, 2020;Chamberlain, 2019). Even though the visibility of systematic compilation studies has been increasing in the physical education and sports literature in recent years as mentioned above, the number of bibliometric studies seems rather limited.…”

Section: The Aim and Significance Of The Studymentioning

confidence: 99%

Mapping Tendencies in Curriculum Research on Physical Education and Sports: A Bibliometric Analysis

ŞAHİN

Karakaya

Dikmen

2023

Participatory Educational Research

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This study aims to investigate previous curriculum research on physical education and sports using the bibliometric mapping method. A systematic map was created for the research tendencies in physical education and sports curricula studies conducted between 1975 and 2021. Accordingly, the intention is to fill a gap in the literature by conducting a general situation analysis about the present status of curriculum studies in physical education and sports based on the publication and citation data obtained from the Web of Science (WoS) database. The software VOSviewer was utilised for the bibliometric analysis. After scanning the studies in the database, 454 studies were accessed at the initial stage. A total of 114 studies were covered in the analysis by following certain exclusion criteria. The findings suggested that curriculum studies in physical education and sports were conducted in association with numerous multidisciplinary research areas. Furthermore, in recent years, a linear increase in curriculum studies has occurred on this subject matter. It was also found that scientists from universities in the United States of America were at the centre of the studies. Another striking result was the limited number of journals specialising in sports and education. The results of the bibliometric maps also demonstrated that the researchers in this field investigated a variety of subjects that can be grouped under four main disciplines: ‘health and physical education,’ ‘curriculum reform,’ ‘contents,’ and ‘pre-service teachers.’ Addedl the results revealed that studies on physical education and sports curricula were conducted with a focus on current developments.

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Beach volleyball athlete training trends of Russian-language scientific resources: a systematic review

Cited by 6 publications

References 37 publications

Simulation Analysis of Physical Fitness Training via Deep Learning Algorithm

Simulation Analysis of Physical Fitness Training via Deep Learning Algorithm

Abdominal Core Strength Training in Female Volleyball Players

Mapping Tendencies in Curriculum Research on Physical Education and Sports: A Bibliometric Analysis

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