Facial recognition multi-dimensional psychosomatic health monitoring system helps campus mental health

Seventeen departments, including the Ministry of Education, issued the notice of the Special Action Plan for Comprehensively Strengthening and Improving the Mental health work of Students in the New Era (2023-2025), which clearly proposed that mental health monitoring should be standardized, and schools should be guided to scientifically standardize the use of evaluation results and establish a "lifetime policy" mental health file. It is necessary to improve psychological early warning intervention, jointly carry out students' mental health education publicity, early detection of students' serious mental health problems, online and offline monitoring and early warning of students' dangerous behaviors such as self-injury or wounding. Therefore, it is important to recognize the signs of suicide in time.

As a new generation of biometric technology in the field of artificial intelligence, the multi-dimensional psychosomatic health monitoring system created by the use of non-contact dynamic physiological and dynamic emotion recognition technology can achieve advance prevention and screening of psychological and emotional abnormalities, so as to prevent them before they happen.

Among them, the rapid emotion screening and early warning analysis system, through non-contact video media, can identify people with potentially dangerous emotions and give early warning when the test object has no obvious perception, which can effectively provide the security department with predictive data and provide the data to other analysis platforms, so that the manager can focus on preventing people with special emotions. Through the psychosomatic health auxiliary judgment system, the hierarchical management of personnel can be realized and the limited resources can be maximized.

The psychological and emotional big data platform can realize the dynamic monitoring and management of personal historical data, team psychological big data, department psychological big data, and the entire enterprise psychological big data. It can display data analysis results such as the number of people who have not punched the card, the pass rate of punching the card, the number and proportion of emotional early warning, the pass rate of twelve-dimensional emotional sub-item, and the early warning chart of comprehensive emotional indicators. To achieve a one-stop solution of psychological and emotional data detection, data early warning, data monitoring and intervention.