Individual classification of elementary school children’s physical activity: A time-efficient, group-based approach to reference measurements

Kühnhausen, Jan; Dirk, Judith; Schmiedek, Florian

doi:10.3758/s13428-016-0724-2

Cited by 14 publications

(14 citation statements)

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“…The results of the study confirm the effectiveness of individual and differentiated approach in working with schoolchildren 8,9,27 . This approach is able to realize the hidden potential of each schoolchild.…”

Section: Discussionsupporting

confidence: 69%

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Development of intellectual abilities of school children with the help of exercise Classics

Polevoy¹

2021

Sri Lanka J Child Health

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Introduction: The problem of intellectual development of schoolchildren can be solved through exercises in physical education classes at school. Objective: To determine the influence of exercise Classics on the development of intellectual abilities of schoolchildren aged 9-10 years. Method: The study was conducted over a period of 9 months, in which forty 9-10 year-olds took part. Physical education classes were held twice a week, each lesson lasting for 40 minutes. The level of development of coordination abilities was assessed on the 'Shuttle run' test, and the indicators of intellectual abilities on the 'Choose unnecessary' test. The programs Bio-Stat 2009, Microsoft Excel 2016 and the student t-test were used for mathematical and statistical processing of results. There were 20 children (12 boys and 8 girls) in the Experimental group (EG) and 20 children (11 boys and 9 girls) in the Control group (CG).Results: Before the beginning of the pedagogical experiment, the indicators of school children in the 2 groups were not significantly different (p>0.05). At the end of the study, the indicators in both groups improved. In the CG, in the 'Shuttle run' test, the indicators improved from 10.2±0.6 to 9.9±0.5 (p>0.05), and in the 'Choose unnecessary' test, the indicators improved by 5.1% (p>0.05). In EG, in the 'Shuttle run 3x10' test, the indicators improved from 9.9±0.5 to 8.5±0.4 (p<0.05), and in the 'Choose unnecessary' test, the indicators improved by 17.5%. These results indicate the _________________________________________

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Section: Discussionsupporting

confidence: 69%

“…Of course, one programme cannot be suitable for every schoolchild. It is important to understand the effectiveness of using an individual and differentiated approach in working with schoolchildren 8,9 . In this regard, there are several opinions about replacing the programme with more modern methods [10][11][12] .…”

Section: Introductionmentioning

confidence: 99%

Development of intellectual abilities of school children with the help of exercise Classics

Polevoy¹

2021

Sri Lanka J Child Health

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“…The developed algorithm was also compared to conventional algorithms using 128 signal points and a processing window size of 2.8 s. For comparison, similar window size classification examples were sought and cited. A similar prior study ( Kühnhausen, Dirk & Schmiedek, 2017 ) adopted SVM for feature classification, demonstrating an overall accuracy of 87.5% using a general model. However, when this conventional SVM algorithm was used with the current data set, its results were worse than those published in the prior study.…”

Section: Discussionmentioning

confidence: 94%

Deep learning-based classification with improved time resolution for physical activities of children

Jang

Kim

et al. 2018

PeerJ

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BackgroundThe proportion of overweight and obese people has increased tremendously in a short period, culminating in a worldwide trend of obesity that is reaching epidemic proportions. Overweight and obesity are serious issues, especially with regard to children. This is because obese children have twice the risk of becoming obese as adults, as compared to non-obese children. Nowadays, many methods for maintaining a caloric balance exist; however, these methods are not applicable to children. In this study, a new approach for helping children monitor their activities using a convolutional neural network (CNN) is proposed, which is applicable for real-time scenarios requiring high accuracy.MethodsA total of 136 participants (86 boys and 50 girls), aged between 8.5 years and 12.5 years (mean 10.5, standard deviation 1.1), took part in this study. The participants performed various movement while wearing custom-made three-axis accelerometer modules around their waists. The data acquired by the accelerometer module was preprocessed by dividing them into small sets (128 sample points for 2.8 s). Approximately 183,600 data samples were used by the developed CNN for learning to classify ten physical activities : slow walking, fast walking, slow running, fast running, walking up the stairs, walking down the stairs, jumping rope, standing up, sitting down, and remaining still.ResultsThe developed CNN classified the ten activities with an overall accuracy of 81.2%. When similar activities were merged, leading to seven merged activities, the CNN classified activities with an overall accuracy of 91.1%. Activity merging also improved performance indicators, for the maximum case of 66.4% in recall, 48.5% in precision, and 57.4% in f1 score . The developed CNN classifier was compared to conventional machine learning algorithms such as the support vector machine, decision tree, and k-nearest neighbor algorithms, and the proposed CNN classifier performed the best: CNN (81.2%) > SVM (64.8%) > DT (63.9%) > kNN (55.4%) (for ten activities); CNN (91.1%) > SVM (74.4%) > DT (73.2%) > kNN (65.3%) (for the merged seven activities).DiscussionThe developed algorithm distinguished physical activities with improved time resolution using short-time acceleration signals from the physical activities performed by children. This study involved algorithm development, participant recruitment, IRB approval, custom-design of a data acquisition module, and data collection. The self-selected moving speeds for walking and running (slow and fast) and the structure of staircase degraded the performance of the algorithm. However, after similar activities were merged, the effects caused by the self-selection of speed were reduced. The experimental results show that the proposed algorithm performed better than conventional algorithms. Owing to its simplicity, the proposed algorithm could be applied to real-time applicaitons.

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“…This study confirms the effectiveness of using a differentiated approach in working with schoolchildren in physical education classes at school. Using this approach in physical education classes, we more effectively develop each schoolchild physical development [5][6]24 .…”

Section: Discussionmentioning

confidence: 99%

“…Despite some flexibility in the work of the program for schoolchildren, it does not sufficiently consider individual and differentiated approaches for younger schoolchildren. This approach allows you to unlock the potential of the schoolchildren, his physical and intellectual abilities and internal reserves of the body [5][6] . Therefore, there are several methodics that the authors suggest to replace the existing standard program [7][8][9] .…”

Section: Introductionmentioning

confidence: 99%

Development of Attention Stability in Children Aged 9-10 years with the Help of Exercises Classics

2021

IJFMT

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Background: the problem of attention stability of schoolchildren can be solved by exercising in physical education classes at school. Aim:To determine the impact of exercise Classics on the development of attention stability in children 9-10 years old.Methods: the study was conducted over a period of 9 months, in which 40 9-10-year-olds took part. Physical education classes were held 2 times a week for 40 minutes each lesson. The level of development of coordination abilities was assessed by the «Shuttle run» test, and the indicators of attention stability by the Methodic «Test Bourdon». The programs bio-stat 2009, Microsoft excel 2016 and t-student were used for mathematical and statistical processing of results.Results: before the beginning of the pedagogical experiment, the indicators of school children between the groups did not have significant differences (P>0.05). After the end of the study, the indicators in both groups improved. In CG, in the «Shuttle run» test, the indicators improved by 2.9% (P>0.05), and in the attention stability test, the indicators improved from 3.5±0.3 to 3.8±0.3 (P>0.05). In EG, in the «Shuttle run 3x10 m» test, the indicators improved from 9.9±0.5 to 8.5±0.4 (P<0.05), and in the «Bourdon test» the indicators improved by 32.4% (P<0.05). These results indicate the effectiveness of using exercise Classics in physical education lessons in working with younger schoolchildren. Conclusion:if schoolchildren perform exercise Classics in physical education classes at school, schoolchildren will improve not only your coordination abilities, but also ability attention stability.

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Individual classification of elementary school children’s physical activity: A time-efficient, group-based approach to reference measurements

Cited by 14 publications

References 58 publications

Development of intellectual abilities of school children with the help of exercise Classics

Development of intellectual abilities of school children with the help of exercise Classics

Deep learning-based classification with improved time resolution for physical activities of children

Development of Attention Stability in Children Aged 9-10 years with the Help of Exercises Classics

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