Comparative Analysis of Cardiorespiratory Parameters of Basketball and Soccer Players Using Principal Component Analysis

IF 0.5 Q4 ENGINEERING, BIOMEDICAL Journal of Biomimetics, Biomaterials and Biomedical Engineering Pub Date : 2022-05-20 DOI:10.4028/p-840n5x
Felipe Sampaio-Jorge, Anderson P Morales, Alexandre Miranda Rodrigues, M. Magini, B. G. Ribeiro
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Abstract

Principal component analysis (PCA) is a statistical technique used to identify variations in multivariate data obtained during the performance of the maximum ergospirometry test (MET). To use the PCA to compare the coefficients of change of the principal component (PC1) using the eigenvalue and the maximum values of the cardiorespiratory variables obtained in the athletes' in MET. 10 soccer players and 10 basketball players, all male, were evaluated. The PCA analyzed the values of the variables during the performance of the MET. The PC1 for each variable was calculated, and the eigenvalue was generated, representing the coefficients of variation of the PC1 of all variables. In the quantitative assessment (maximum values), a higher VO2max (3.93±0.62 vs. 3.41±0.37 l·min-1) was observed in basketball players compared to soccer players (p<0.05). The qualitative evaluation using PC1 of cardiorespiratory parameters (heart rate, minute volume, O2 consumption, CO2 production, expired fraction of O2 and expired fraction CO2) was observed as an eigenvalue (6.50±0.27 vs. 6.22±0.19) high for basketball players compared to soccer players (p<0.05). It is concluded that the basketball players showed more significant variability in their cardiorespiratory variables during the performance of the MET and higher VO2max at the end of the MET. These findings indicate that basketball players were less efficient in buffering the ventilatory acidosis observed during the MET. The results of this study highlight the importance of making complex assessments of the cardiorespiratory system, providing qualitative information to complement the quantitative data.
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篮球运动员与足球运动员心肺参数的主成分分析比较
主成分分析(PCA)是一种统计技术,用于识别在进行最大肺活量测试(MET)期间获得的多变量数据的变化。使用主成分分析,使用运动员在MET中获得的心肺变量的特征值和最大值来比较主成分(PC1)的变化系数。对10名足球运动员和10名篮球运动员进行了评估,他们都是男性。主成分分析对MET执行过程中的变量值进行了分析。计算每个变量的PC1,并生成本征值,表示所有变量PC1的变异系数。在定量评估(最大值)中,与足球运动员相比,篮球运动员的VO2max更高(3.93±0.62 vs.3.41±0.37 l·min-1)(p<0.05)。使用PC1对心肺参数(心率、分钟容量、O2消耗、CO2产生、O2过期分数和CO2过期分数)的定性评估被观察为篮球运动员的特征值(6.50±0.27 vs.6.22±0.19)高结果表明,篮球运动员在MET表现期间心肺变量的变异性更大,在MET结束时VO2max更高。这些发现表明,篮球运动员在缓冲MET期间观察到的通气性酸中毒方面效率较低。这项研究的结果强调了对心肺系统进行复杂评估的重要性,提供了定性信息来补充定量数据。
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CiteScore
1.40
自引率
14.30%
发文量
73
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