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INTRODUCTION: The widespread use of smart wearable devices in various fields, including healthcare and sports, underscores the importance of their application in enhancing physical exercise among college students. Recent advancements in technology have facilitated the development of sophisticated methods to assess and predict physical activity outcomes, making their evaluation increasingly critical. OBJECTIVES: This study aims to develop a reliable assessment model for smart wearable devices used in college students' sports activities. The objective is to accurately predict and evaluate the effectiveness of these devices in improving students' physical health and promoting lifelong sports habits. Ultimately, the research seeks to integrate advanced computational methods to enhance the accuracy of physical exercise assessments. METHODS: The research introduces a novel assessment model that combines a zebra behavior-based heuristic optimization algorithm with a convolutional neural network (CNN). By analyzing user behavior data from wearable devices, the model constructs an evaluation index system tailored for college sports activities. The approach optimizes the parameters of the CNN using the zebra optimization algorithm, ensuring enhanced prediction accuracy. RESULTS: The evaluation model demonstrated high accuracy, with a significant improvement in predicting the outcomes of physical exercises among college students. Comparative analyses with traditional methods revealed that the new model reduced prediction errors and increased real-time performance metrics. Specifically, the model achieved a lower root mean square error (RMSE) in simulation tests, indicating more precise assessments. Figures and statistical data provided in the study illustrate the model's superior performance across various parameters. CONCLUSION: The developed assessment model significantly advances the application of smart wearable devices in monitoring and enhancing college students' physical activities. By integrating cutting-edge algorithms, the study not only improves the accuracy of exercise assessments but also contributes to the broader understanding of technology's role in health and fitness education. Future research could further refine this model by incorporating additional sensors and data points to expand its applicability and robustness. [ABSTRACT FROM AUTHOR]

In the realm of obesity and overweight, the risk of chronic diseases significantly escalates, closely intertwined with inflammatory factors. Research suggests that specific exercise interventions, particularly aerobic exercise and resistance exercise, can have beneficial effects on inflammation levels. However, debates persist regarding the actual impact of exercise in the obese and overweight population. We employed meta-analysis research methods and searched the China National Knowledge Infrastructure Wanfang Data, PubMed, and Web of Science databases to gather controlled experiments on the effects of resistance exercise or aerobic exercise on C-reactive protein (CRP), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α). Two researchers independently conducted literature screening and data extraction. The quality of the literature was assessed according to the Cochrane Handbook standards, and subgroup analyses of CRP, IL-6, and TNF-α were performed using RevMan 5.4 software. Through quantitative synthesis of results from 22 selected studies encompassing a total of 1,135 research subjects, this study systematically explored the specific regulatory effects of different exercise modalities on inflammatory markers in the obese and overweight population. The findings indicate that both aerobic exercise and resistance exercise effectively reduce CRP levels in obese individuals, with aerobic exercise demonstrating a more pronounced effect. Aerobic exercise also significantly lowers IL-6 levels, while the impact of resistance exercise on IL-6 is relatively minor. However, in terms of reducing TNF-α levels, neither modality appears to exert a significant effect. Overall, exercise, especially aerobic exercise, emerges as a positive regulator of inflammatory markers in the context of obesity and overweight.