基于肌肉协同模式评估和提高运动员表现的新方法:设计生物反馈训练方案的新方法

Armin Hakkak Moghadam Torbati, Mohammadamin Gholibeigi, S. Jami
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引用次数: 0

摘要

目标:对于任何水平的运动员来说,达到他们的终极表现都是一个巨大的挑战。根据运动控制理论,在准备锻炼的最后阶段对运动进行精确的规划可以提高运动员的表现。因此,本研究旨在设计一种性能分析方法,用于对运动员进行分类,并在运动过程中给予反馈。这样,运动员和教练员就可以考虑运动方案来调整和改善运动员的表现。方法:参与者由20名年龄在25 - 30岁之间的男性组成。这些对象包括10名职业足球运动员和10名业余足球运动员。所有专业和业余运动员连续6天进行相同的试验。为所有参与者设计了两种不同类型的条件。在前三天,受试者被要求像在比赛中一样在实际情况下罚点球10次(足球运动员)。这些程序都是在模拟条件下完成的,在接下来的三天里由电脑(Xbox)设计。在试验期间记录腓肠肌和胫骨前肌的表面肌电图。结果:结果显示,所有专业被试在真实和游戏两种情况下,基向量之间的最大误差分别为0.48和0.37(均方误差指数),相对于数据范围(5.1)而言,这是非常低的。相比之下,业余运动员在两种情况下的最小误差分别为13.18和18.72,与数据范围相比,这是一个很大的误差(7)。讨论:在两种情况下,职业运动员总是以相同的方式使用肌肉。事实上,专业运动员的肌肉会因为轻微的错误而遵循特定的模式,而业余运动员的肌肉则不会。
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New Method to Assess and Enhance Athletes’ Performance Based on Muscle Synergy Patterns: A New Approach to Design a Biofeedback Training Scheme
Objectives: There has been a big challenge for athletes at any level to reach their ultimate performance. According to a Motor Control theory, accurate programming of movements during the last stage of preparation to work out can improve athletes' performance. So, this study aims to design a performance analysis method that can be used to classify athletes and give them feedback during exercise. In this way, athletes and coaches can consider exercise schemes to modify and ameliorate athletes' performance.  Methods: The participants were made up of 20 men between 25 to 30 years old. These subjects include ten professional football players and ten amateur football players. The same trials in 6 successive days were done by all athletes, both professional and amateur. Two different types of conditions were designed for all participants. In the first three days, subjects were asked to shoot a penalty kick (football player) 10 times in an actual situation like what they do in a competition. These procedures were done in the simulation condition, in the next three days designed by the computer (Xbox). Surface electromyography (sEMG) was recorded from the gastrocnemius and tibialis anterior muscles during trials. Results: Results showed the maximum error between basis vectors in all of the professional subjects in each situation, real and game, were 0.48 and 0.37, respectively (Mean square error index), which are very low relative to the range of data (5.1). In contrast, the minimum error among amateurs in each situation was 13.18 and 18.72, which are a high amount compared with the range of data (7).  Discussion: Professional athletes always, in both situations, use their muscles in the same way. In fact, professional athletes' muscles follow specific patterns due to slight errors, while amateurs' muscles do not.
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来源期刊
Central European Journal of Sport Sciences and Medicine
Central European Journal of Sport Sciences and Medicine Business, Management and Accounting-Tourism, Leisure and Hospitality Management
CiteScore
0.60
自引率
0.00%
发文量
9
审稿时长
12 weeks
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