4053914

Physiological and biochemical monitoring of athletes` training based on scientific knowledge map

In order to maximize the potential of athletes, maintain the best competitive state and scientifically arrange training programs, it is necessary to establish a set of special training physiological and biochemical monitoring methods suitable for swimming long distance projects to ensure the scientific development of swimming training. But so far, no relevant research reports have been seen in China. The development of computer technology has attracted more and more attention to the deep mining of data. At the same time, it has greatly promoted the progress of information visualization technology and social network analysis. Therefore, the technology of scientific knowledge map is also in operation. Therefore, based on the perspective of scientific knowledge map, this research uses the literature data method, expert interview method, scientific knowledge map method, cluster analysis method and other methods to analyze the physiological and biochemical monitoring theory research in the training process of domestic and foreign athletes. In this study, we analyzed the time distribution characteristics of the research literature on the monitoring of physiological and biochemical indicators during the training process, the co-occurrence map of keywords, the research frontier and the recent analysis of physiological and biochemical monitoring indicators. Integrate the contents of the analysis into the training process of athletes, and based on the existing research hotspots, continue to carry out extensive theoretical research in the field of competitive swimming.
© Copyright 2019 Investigación Clínica. Universidad del Zulia. All rights reserved.

Bibliographic Details
Subjects:
Notations:biological and medical sciences training science
Published in:Investigación Clínica
Language:English
Published: 2019
Online Access:http://www.clinicajournal.com/index.php/path/article/download/763/761
Volume:60
Issue:3
Pages:555-567
Document types:article
Level:advanced