Construction and Development Strategy of an Application System of Intelligent Sports in China’s Sports Industry

Tang, Yuxin; Zan, Shengfeng; Zhang, Xiaowen; Zhu, Wei

doi:10.1155/2022/3688261

Cited by 2 publications

(1 citation statement)

References 26 publications

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“…At its core, a talent cultivation system emphasizes a structured and holistic approach to athlete development [3]. It begins with the identification of promising talent through comprehensive scouting, assessment, and data analysis [4]. This phase involves evaluating physical attributes, technical skills, mental fortitude, and other factors relevant to athletic performance.…”

Section: Introductionmentioning

confidence: 99%

Construction and Optimization of Sports Athlete Selection and Talent Cultivation System Based on Data Analysis

Zhuoxiao Liu

2024

jes

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Talent cultivation is the deliberate and systematic process of identifying, nurturing, and developing individuals' innate abilities and potential across various domains. It involves providing structured opportunities, resources, and guidance to help individuals flourish and excel in their chosen fields. This process encompasses education, mentorship, training programs, and practical experiences tailored to the specific needs and interests of each individual. This paper presents a novel approach to the construction and optimization of a Sports Athlete Selection and Talent Cultivation System through the integration of data analysis techniques, with a particular emphasis on the Anthropometric Invariance Gait Recognition for Pattern (AIGRP) system. Leveraging advanced algorithms, the AIGRP system enables precise characterization of athletes' biomechanical profiles based on anthropometric measurements and gait characteristics. By analyzing data collected from athletes, including age, gender, height, weight, and specific performance metrics, such as speed, strength, and endurance, the system facilitates personalized athlete selection and talent cultivation strategies. Furthermore, the objective and data-driven nature of the AIGRP system reduces biases inherent in traditional selection methods, leading to more efficient and effective talent identification. By analyzing data collected from athletes, including age, gender, height (mean: 175 cm), weight (mean: 70 kg), and specific performance metrics, such as speed (mean: 6.5 m/s), strength (mean: 140 kg), and endurance (mean: 47 min), the system facilitates personalized athlete selection and talent cultivation strategies.

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Section: Introductionmentioning

confidence: 99%

Construction and Optimization of Sports Athlete Selection and Talent Cultivation System Based on Data Analysis

Zhuoxiao Liu

2024

jes

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A Smart Ski Pole for Skiing Pattern Recognition and Quantification Application

Guo,

Ju,

et al. 2024

Sensors

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In cross-country skiing, ski poles play a crucial role in technique, propulsion, and overall performance. The kinematic parameters of ski poles can provide valuable information about the skier’s technique, which is of great significance for coaches and athletes seeking to improve their skiing performance. In this work, a new smart ski pole is proposed, which combines the uniaxial load cell and the inertial measurement unit (IMU), aiming to provide comprehensive data measurement functions more easily and to play an auxiliary role in training. The ski pole can collect data directly related to skiing technical actions, such as the skier’s pole force, pole angle, inertia data, etc., and the system’s design, based on wireless transmission, makes the system more convenient to provide comprehensive data acquisition functions, in order to achieve a more simple and efficient use experience. In this experiment, the characteristic data obtained from the ski poles during the Double Poling of three skiers were extracted and the sample t-test was conducted. The results showed that the three skiers had significant differences in pole force, pole angle, and pole time. Spearman correlation analysis was used to analyze the sports data of the people with good performance, and the results showed that the pole force and speed (r = 0.71) and pole support angle (r = 0.76) were significantly correlated. In addition, this study adopted the commonly used inertial sensor data for action recognition, combined with the load cell data as the input of the ski technical action recognition algorithm, and the recognition accuracy of five kinds of cross-country skiing technical actions (Diagonal Stride (DS), Double Poling (DP), Kick Double Poling (KDP), Two-stroke Glide (G2) and Five-stroke Glide (G5)) reached 99.5%, and the accuracy was significantly improved compared with similar recognition systems. Therefore, the equipment is expected to be a valuable training tool for coaches and athletes, helping them to better understand and improve their ski maneuver technique.

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Construction and Development Strategy of an Application System of Intelligent Sports in China’s Sports Industry

Cited by 2 publications

References 26 publications

Construction and Optimization of Sports Athlete Selection and Talent Cultivation System Based on Data Analysis

Construction and Optimization of Sports Athlete Selection and Talent Cultivation System Based on Data Analysis

A Smart Ski Pole for Skiing Pattern Recognition and Quantification Application

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