With the continuous development of science and technology, people can apply more and more technology to the cultivation of children’s abilities. In the process of cultivating children’s ability, the most fancy is the study of executive function, and this is the research topic of this article. In the past, training methods such as music, mindfulness, and exercise have been used in the study of children’s executive abilities to promote the development of preschool children’s executive functions. While various approaches have had some effect, researchers have been exploring more comprehensive approaches to effective training. This article is aimed at studying how to use image recognition technology to conduct an intervention analysis of breakdancing in promoting the executive function of preschool children. For this reason, this paper proposes image recognition technology based on deep learning neural network and conducts research, analysis, and improvement on related technologies obtained from deep learning. This makes it more suitable for the research topic of this article and design-related experiments and analysis to explore its related performance. The experimental results in this paper show that the improved image recognition technology has improved accuracy by 31.2%. And the performance of its algorithm is also improved by 21%, which can be very effective in monitoring preschool children during breakdancing.

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Cognitive control is essential to daily life. Task switching is a classical paradigm used to study cognitive control. Previous researchers have studied the representation of different abstract hierarchical rules in the prefrontal cortex and explored the process mechanisms of task switching. However, the differences between the different hierarchical levels of task switching, especially the related neural mechanisms in the prefrontal cortex, are still unclear. This review focuses on and summarizes this issue. The present study suggests that the higher the hierarchical rule shifting or task switching, the more anterior the activation is on the prefrontal cortex. In addition, a high hierarchy of rules or tasks is more abstract, which leads to a larger switching cost.

In recent years, with the rise of virtual and sports, people are often injured due to irregular movements during exercise. Based on this, this article takes the basic concept of computer virtual reality as the starting point and analyzes the adoption of computer virtual reality in sports correction. The choice of corrective exercises depends on the daily wrong exercises. If there is an error in any operation, please select the corresponding operation mode for the error operation for corrective training. If there are multiple errors at the same time, we compare and select the error operation that needs to be resolved first and the error operation that needs to be resolved later. In our daily life, the squat action pattern of Tai Chi Half-squat stance ball is closely related to us, and its action pattern can fully reflect the core stability of the subject. In this study, 42 students were selected as the students of a college sports college in Dalian. There are 7 people in each group, divided into 6 groups. The first three groups used exercise correction to assist the traditional teaching method (experimental group). It was found that the performance error rate of the first three groups reached 65%, and the last three groups used the assisted virtual reality teaching method, and the error rate was only 4%. Therefore, we adopted the teaching of virtual reality can reduce the error rate of the movement posture. We trained them for half a year and assessed and scored them once a month. We collect this data and analyze it to reach a conclusion. The experimental results prove that the experimental group has a significant difference before and after the squat test ( P < 0.05 ), and postexperiment there is a remarkable disparity among the experimental group and the comparison group ( P < 0.05 ). Therefore, squatting correction training is effective in improving the wrong squat. It is very effective for problems such as posture movement mode and joint limitation. Therefore, it is a very meaningful thing to explore the exercise correction training based on the virtual reality of computer vision.

Introduction: Core strength training focuses mainly on the muscle group and neuromuscular system of the central area of the human body to gain strength and stability for complex movements. Studies have reported the effect of core training on high-capacity athletes, but there is still a gap regarding the impacts on physical capacity in running athletes. Objective: To study the effects of strength training on athletes’ core and the direct impacts on running quality. Methods: Athletes of the men’s running team at the athletic training center of the Institute of Physical Education were core strength trained for 10 to 12 weeks. After the period, physical tests, according to predetermined protocols. The data were compared before, after the intervention, and after statistical treatment, and the findings were discussed according to the scientific literature. Results: After 12 weeks of training, among the five sports skills, there was only a significant difference before and after training of body lateral flexion (right side) (P<0.05), and there was no significant difference before and after training of the other four sport skills (P > 0.05). Conclusions: Through the static and dynamic exercises of core strength training, we can effectively improve the proprioception intervention in body movement so that runners can more accurately control their joints and muscles, ensuring movement and postural accuracy. Level of evidence II; Therapeutic studies - investigation of treatment outcomes.