Design and mental health enhancement strategies of students’ emotional intervention model in physical education supported by intelligent algorithms

Appropriate use of emotions as a means to intervene in students' sports behaviors in physical education can promote individuals to form correct concepts of sports and physical exercise.In this paper, in order to construct an emotion intervention model, a cross-temporal adaptive graph convolution network (CST-AGCN) model for whole-body limb emotion recognition is proposed by using the method of spatio-temporal graph convolution.The model was applied to the first stage of negative emotion intervention, after which the appropriate intervention strategy was selected from the intervention strategy library.Then the system was used to assist the teacher in completing some of the intervention initiatives.Finally, based on the empirical study and the system, the learners' classroom status after the intervention was analyzed again.In addition the study also designed strategies related to enhancement of students' mental health to further promote students' physical and mental health.After applying the emotional intervention model and mental health enhancement strategies to the second year (1) class of Secondary School S, this group of students showed significant differences in subjective experience, emotional vitality, body value, interpersonal perception, and dilemma coping, and their mental health was significantly improved.Physical education scores were 7.96 points higher compared to the traditional teaching class, and anxiety decreased significantly.It indicates that the intervention model and mental health enhancement strategies in this study can reduce students' anxiety behavior and have a more significant relief of students' negative emotional symptoms such as anxiety and depression, thus promoting the quality of physical education teaching.