Objective. To investigate the effects of 12-week physical exercise (jogging, basketball, and outdoor training) on sleep quality, harmful mood, and heart rate variability (HRV) in college students with Internet addiction. Methods. 46 college students with Internet addiction were chosen and then randomly assigned to the Internet addiction group (IA, n = 23 ) and the Internet addiction exercise group (IA+EX, n = 23 ). The subjects in the IA+EX group underwent physical exercise for 12 weeks (three times per week), and the IA group did not perform regular physical exercise during the experiment. Then, the degree of Internet addiction, depression, and sleep quality were evaluated by using Young’s Internet Addiction Test (IAT) scale, Center for Epidemiologic Studies Depression (CES-D) scale, and Pittsburgh sleep quality index (PSQI); HRV were measured by using Polar Team 2 before and after physical exercise intervention. Results. (1) After the 12-week exercise, compared to preexercise intervention, the scores of IAT, CES-D, and PSQI significantly decreased ( t = 12.183 , 9.238, 5.660; P < 0.01 ) in the IA+EX group; compared with the IA group, the scores of IAT, CES-D, and PSQI significantly decreased ( t = 2.449 , 3.175, 4.487; P < 0.05 , P <0.01) in IA+EX group college students with Internet addiction. (2) After the 12-week exercise, compared to preexercise intervention, LFn and the ratio of LF/HF significantly decreased ( t = 5.650 , 3.493; P < 0.01 ) and HFn significantly increased ( t = − 2.491 , P < 0.05 ) in the IA+EX group; there were no significant differences in the above indexes before and after the experiment in the IA group ( P > 0.05 ). Compared with the IA group, HFn significantly increased ( t = 3.616 , P < 0.01 ) and the ratio of LF/HF significantly decreased ( t = 2.099 , P < 0.01 ) in IA+EX group college students with Internet addiction; there was no significant difference in LFn between the two groups. Conclusion. Long-term physical exercise could significantly reduce the degree of Internet addiction and depression, improve sleep quality, and balance sympathetic parasympathetic function of college students with Internet addiction, indicating that exercise-based intervention might be an effective way to alleviate or even eliminate Internet addiction.

In order to improve the training effect of athletes and effectively identify the movement posture of basketball players, we propose a basketball motion posture recognition method based on recurrent deep learning. A one-dimensional convolution layer is added to the neural network structure of the deep recurrent Q network (DRQN) to extract the athlete pose feature data before the long short-term memory (LSTM) layer. The acceleration and angular velocity data of athletes are collected by inertial sensors, and the multi-dimensional motion posture features are extracted from the time domain and frequency domain, respectively, and the posture recognition of basketball is realized by DRQN. Finally, the new reinforcement learning algorithm is trained and tested in a time-series-related environment. The experimental results show that the method can effectively recognize the basketball motion posture, and the average accuracy of posture recognition reaches 99.3%.

Competitive performance ability is the on-the-spot performance of basketball players’ comprehensive use of technical and tactical, physical, and psychological abilities. Because basketball players’ competitive performance includes many evaluation contents and influencing factors, it is difficult to comprehensively and objectively use a single qualitative analysis or quantitative statistics for evaluation and measurement. Based on the analytic hierarchy process (AHP) and intelligent fuzzy comprehensive evaluation, this research establishes a hybrid model, which is applied to evaluate the performance of basketball players. Based on the actual needs, this research uses the relevant theories in the discipline of sports training, with abundant empirical data materials, combined with the specific practice of basketball players’ training and competition, starting from the concept of clear sports intelligence, to further determine the indicators of the basketball players’ sports intelligence evaluation system and weights, construct a set of evaluation system about basketball players, and use this as a standard to evaluate and judge the current situation of basketball players’ sports intelligence.