Hydration Status in Adolescent Alpine Skiers During a Training Camp

IMPROVEMENT OF PHYSICAL CONDITIONS IN TENNIS PLAYERS UNDER HIGH ALTITUDES

ABSTRACT Introduction: Due to the lower atmospheric density at high altitudes, the spherical surface of the table tennis ball offers less resistance, requiring higher performance from its players. The athletes' reaction time and movement speed can improve significantly. Objective: This paper studies the changes in the fitness level of Chinese table tennis players under training at high altitudes. These results can serve as a reference to formulate and implement the training strategy of the Chinese table tennis team. Methods: The performance of 12 outstanding table tennis players in the competition was explored. After arriving at the high altitude, the athletes practiced training for four weeks. The athletes' biochemical parameters and heart rates were evaluated before and after training. These data were statistically treated. Results: The heart rate of the athletes in the third week after the experiment was lower than before, with no significant difference (P>0.05). The hematocrit value of table tennis players in training showed a temporary elevation after one week, significantly different from that before the experiment (P<0.05). After two weeks of exercise at a high altitude, the hematocrit value of the athletes remained at a high level (P<0.05). Conclusion: Table tennis players can improve their physical conditions with training at high altitudes, including aerobic and anaerobic properties. High-intensity exercise at high altitudes is also beneficial for improving athletes' strength, speed, and reaction time quality. Level of evidence II; Therapeutic studies - investigating treatment outcomes.

Analysis of Human Exercise Health Monitoring Data of Smart Bracelet Based on Machine Learning

The smart bracelet has become a hot-selling commodity, according to a daily consumption survey. Based on people's interest and concern for their health, the smart bracelet, as a design and application for achieving healthy weight loss monitoring, is quickly becoming a popular new favorite. This bracelet detects fat using the near-infrared diffuse reflection principle, with the goal of assisting people in controlling and maintaining a healthy weight. A large amount of data has been accumulated in all walks of life due to the development of the Internet network and data storage technology. As a result, the emergence of machine learning plays a critical role in the data analysis of human sports health monitoring of smart bracelets. Based on machine learning, this paper investigates the data analysis of human sports health monitoring smart bracelets. When the population index reaches 50 in the analysis of health monitoring data, the average accuracy of data mining is 86.8 percent, the average accuracy of the association rule algorithm is 85.9 percent, the average accuracy of the collaborative filtering algorithm is 84.3 percent, and the average accuracy of the machine learning algorithm is 90.1 percent in this paper. Among the four algorithms, the method presented in this paper is clearly the most effective, stable, and accurate. The system's stability and accuracy have been greatly improved by the addition of GPS-assisted and hand-up misjudgment algorithms. Because the smart bracelet is inexpensive, easy to wear, and consistent with consumer psychology, it is becoming increasingly popular to use it to monitor the human body's sports health.