At present, the field of campus student health detection and analysis is constantly developing with the help of big data technology. On the basis of collecting multi-source data, this paper takes students on campus as the research object for data processing and analysis, and uses data mining and machine learning algorithms to carry out in-depth research. The results show that: (1) Big data technology has been paid more and more attention in campus student health detection and analysis, but it still faces challenges in the application process such as data privacy protection and data security; (2) Campus students' health data mainly come from health examination records, sports activity data and other aspects; (3) Through the construction of student health file system, students' health status can be revealed in multiple dimensions, and targeted management and intervention measures are proposed. The application of big data technology is conducive to the intelligent and personalized campus health management.
physical and mental health; heart rate; bmi; cardiopulmonary function; blood oxygen content
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