Analysis of the Characteristics of Thinking Control during Basketball Free Throw Based on Electroencephalogram

Su, Jiaben; Yang, Bo

doi:10.14704/nq.2018.16.5.1272

Cited by 4 publications

(2 citation statements)

References 8 publications

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“…This requires athletes to analyze their shot speed and angle in their daily free throw training and combine them with their physical conditions to find out the free throw technique that is closest to the theoretical shot speed and angle.Guochen, W et al designed a shooting framework based on a multi-camera detection algorithm to achieve precise positioning of the basket and assist athletes' shooting training and confirmed the effectiveness of the method through practical application [9]. Su, J. et al investigated the influencing factors of free throw shooting rate from the angles of athlete's psychology, physiology, and basketball technique, which provided an essential reference for the study of basketball players' free throw shooting rate [10]. Rong, J. used a sampling experimental method to investigate the changes in free throw eye movements and brain-related potentials and pointed out that the free throw shooting accuracy could be improved by training athletes' free throw gazing behavior [11].…”

Section: Introductionmentioning

confidence: 93%

Teaching the process of free throw action in basketball course based on motion vector field transformation

Li,

2024

Applied Mathematics and Nonlinear Sciences

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In order to improve the teaching quality of the free throw action process in basketball courses, this paper proposes research on the teaching of free throw action by integrating motion vector field transformation. Starting from the actual situation of the player’s free throw action, it describes the problems in the teaching process of free throw action. It elaborates on the structure and principle of the motion vector field transformation algorithm in depth. In video analysis teaching of free-throw shooting action processes, the player’s motion vectors can easily be interfered with by random noise, which needs to be optimized using smoothing processing and compensation models. Combined with the teaching objectives of free throw action, the design and development of the “basketball free throw action” microteaching by integrating the motion vector field transformation through the analysis of a university sports college basketball class of 2021 students found that from the seventh week and the eighth week of the experimental group and the control group, respectively, there is a difference of 7.8% and 13%. The ball-hitting rate is significantly different from that of the control group (<0.5). A significant difference occurred (<0.05). Although both methods have improved the free throw shooting rate of the athletes, the teaching of free throw shooting action in the basketball course integrating the motion vector field transformation performs better compared to the traditional free throw shooting action teaching mode. This study provides technical support and diversified media presentation methods for the design and development of basketball micro-courses. It constructs a feasible way to develop and innovate college basketball teaching.

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Section: Introductionmentioning

confidence: 93%

Teaching the process of free throw action in basketball course based on motion vector field transformation

Li,

2024

Applied Mathematics and Nonlinear Sciences

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“…It must be highlighted that not all of the authors held biomechanical factors as the dominant with regards to improving the effectiveness of a free throw in basketball. Some of the authors selected the players' psyche as the decisive element (Gomez, Kreivyte, Sampalo, 2017;Oancea, Ionescu, 2015;Ocak et al, 2014;Su, Yang, 2018). The amount of literature addressing this element shows how important it is within the game.…”

Section: Stability Training and Effectiveness Of Playing Basketballmentioning

confidence: 99%

Stability Training and Effectiveness of Playing Basketball

Worobel

2020

Central European Journal of Sport Sciences and Medicine

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The aim of this study is to review the available literature for factors affecting a basketball throw and the stabilization of the trunk. Searching for the most important elements which ought to be improved during training to increase the effectiveness of a throw and those which condition the correct stabilization of the trunk. The obtained results, after analyzing the literature, show that it is not possible to determine a single factor affecting a throw and the stabilization of the trunk. There are many factors that influence each other and, therefore, must be trained as one. There are biomechanical relationships between the effectiveness of making a throw, the positioning of the limbs, the trunk and the trajectory of the ball. It is important to mention the role of a factor outside biomechanics, such as the player's psyche. Muscles have the greatest impact on stabilization. Muscle function would not be possible without proper control by the nervous system The conclusion section shows a large number of interacting factors responsible for the quality and effectiveness of the throw as well as for the stabilization of the trunk. This allows better planning and conducting of basketball training aimed at improving technique and throw effectiveness.

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Deep Learning-based Basketball Free Throw Attitude Analysis and Hit Probability Prediction System Research

Zhao

2024

Applied Mathematics and Nonlinear Sciences

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Traditional basketball free-throw hitting probability prediction mainly relies on naked eye vision to analyze basketball players, which makes it difficult to achieve stable and accurate free-throw hitting probability prediction. In this study, we propose a deep learning-based algorithm for recognizing basketball free throw poses and predicting the probability of hitting free throws, and we build a corresponding system framework. DetectNet is used to screen free throw motion detectors, real-time estimate and recognition of free throw poses, and code rewriting. At the same time, Open Pose is used as a human skeletal joint point detector to extract the joint point information of the free throw shooter. The joint points with wrong information are repaired, and the classification prediction of the free throw hitting result is realized based on the support vector machine. In the performance simulation experiments, the average accuracy of the free throw pose recognition method proposed in this paper is as high as 98.55% on the MSR Action 3D dataset, and the recognition rate of the elbow lift pose, which is the most difficult to recognize, is also higher than that of other comparative algorithms. The hit probability prediction method is also 12.64% and 6.25% more accurate than the OpenPose algorithm in hit-and-miss prediction, and the accuracy has also improved by 4.47% and 5.41%, respectively. The free throw pose recognition and hit probability prediction method in this paper has excellent performance.

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Analysis of the Characteristics of Thinking Control during Basketball Free Throw Based on Electroencephalogram

Cited by 4 publications

References 8 publications

Teaching the process of free throw action in basketball course based on motion vector field transformation

Teaching the process of free throw action in basketball course based on motion vector field transformation

Stability Training and Effectiveness of Playing Basketball

Deep Learning-based Basketball Free Throw Attitude Analysis and Hit Probability Prediction System Research

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