Ding Lihe, Yuan Lei-Ming, Sun Yiye, Zhang Xia, Li Jianpeng, Yan Zou
School of Physical Education & Sport Science, Wenzhou Medical University, Wenzhou 325035, China.
College of Electric & Electronic Engineering, Wenzhou University, Wenzhou 325035, China.
J Anal Methods Chem. 2020 Aug 29;2020:8828213. doi: 10.1155/2020/8828213. eCollection 2020.
Athletes usually take nutritional supplements and perform the specialized training to improve the performance of sport. A quick assessment of their athletic status will help to understand the current physical function of athletes' status and the effect of nutritional supplementation. Human urine, as one of the most important body indicators, is composed of many metabolites, which can provide effective monitoring information for physical conditions. In this study, temperature-dependent near-infrared spectroscopy (NIRS) technology was used to collect the spectra of athlete's urine for evaluating the feasibility of rapidly detecting the exercise state of the basketball player. To obtain the detection results accurately, several chemometrics methods including principal component analysis (PCA), variables selection method of variable importance in projection (VIP), continuous 1D wavelet transform (CWT), and partial least square-discriminant analysis (PLS-DA) were employed to develop a classifier to distinguish the physical status of athletes. The optimal classifying results were obtained by wavelet-PLS-DA classifier, whose average precision, sensitivity, and specificity are all above 0.95, and the overall accuracy of all samples is 0.97. These results demonstrate that temperature-dependent NIRS can be used to rapidly assess the physical function of athlete's status and the effect of nutritional supplementation is feasible. It can be believed that temperature-dependent NIR spectroscopy will obtain applications more widely in the future.
运动员通常会服用营养补充剂并进行专项训练以提高运动成绩。快速评估他们的运动状态有助于了解运动员当前的身体机能状况以及营养补充的效果。人体尿液作为最重要的身体指标之一，由许多代谢物组成，能够为身体状况提供有效的监测信息。在本研究中，采用温度依赖近红外光谱（NIRS）技术收集运动员尿液的光谱，以评估快速检测篮球运动员运动状态的可行性。为了准确获得检测结果，采用了几种化学计量学方法，包括主成分分析（PCA）、投影变量重要性变量选择方法（VIP）、连续一维小波变换（CWT）和偏最小二乘判别分析（PLS-DA）来开发一个分类器，以区分运动员的身体状态。通过小波-PLS-DA分类器获得了最佳分类结果，其平均精度、灵敏度和特异性均高于0.95，所有样本的总体准确率为0.97。这些结果表明，温度依赖NIRS可用于快速评估运动员的身体机能状况以及营养补充的效果是可行的。可以相信，温度依赖近红外光谱在未来将得到更广泛的应用。
