Research Article
Automatic Assessment Method of College Students Psychological Stress Based on Medical Big Data
@INPROCEEDINGS{10.1007/978-3-031-33545-7_5, author={Xiang Li}, title={Automatic Assessment Method of College Students Psychological Stress Based on Medical Big Data}, proceedings={IoT and Big Data Technologies for Health Care. Third EAI International Conference, IoTCare 2022, Virtual Event, December 12-13, 2022, Proceedings}, proceedings_a={IOTCARE}, year={2023}, month={5}, keywords={Medical Big Data College Students’ Psychology Psychological Stress Evaluation Methods}, doi={10.1007/978-3-031-33545-7_5} }- Xiang Li
Year: 2023
Automatic Assessment Method of College Students Psychological Stress Based on Medical Big Data
IOTCARE
Springer
DOI: 10.1007/978-3-031-33545-7_5
Abstract
Students’ psychological stress assessment has become an important part of college mental health management, but the current assessment methods are qualitative analysis, combined with the scale to get the assessment results. The lack of data support in the evaluation process leads to large evaluation errors. In view of the above practical problems, this paper studies the automatic evaluation method of college students’ psychological stress based on medical big data. After using crawlers to obtain medical big data, it was preprocessed. Taking physiological data as the evaluation index of psychological stress, the relationship between physiological indexes and psychological stress is obtained by data mining. The HMM model improved by SVM is used to quantify the evaluation results. After testing, the relative error of the evaluation method based on medical big data is less than 10%, and the evaluation accuracy is higher.
