The Design and Application of College Students’ Mental Health Automatic Evaluation Model Based on Multimodal Data Fusion

With the continuous increase of people’s work pressure, the requirements for mental health recognition are also higher and higher. There are various forms of mental health, and the traditional mental health evaluation mode relying on experts has certain subjective deviation. Therefore, this paper proposes a recognition model based on facial, speech and gait behavior characteristics to realize intelligent recognition of mental health status, so as to reduce the impact of subjective factors on the recognition results. The design of automatic evaluation model of College Students’ mental health. The purpose of this study is to design an automatic evaluation system, which can evaluate the mental health of college students in a simple and easy way through their writing performance. In order to achieve this goal, we adopted two methods: (1) according to the concept that each writer has his own style and personal characteristics, we compiled a self-assessment questionnaire; (2) This study uses the data collected in previous studies on writers’ styles and personality characteristics.