Research on Portable Intelligent Terminal and APP Application Analysis and Intelligent Monitoring Method of College Students' Health Status

Yu Li; Yuetong Gao

doi:10.4108/eetpht.10.5899

Authors

Yu Li College of Vocal Language and Art Sichuan University of Media and Communications, Chengdu 510117, Sichuan, China
Yuetong Gao College of Digital Arts Chengdu Vocational University of The Arts, Chengdu 510132, Sichuan, China

DOI:

https://doi.org/10.4108/eetpht.10.5899

Keywords:

portable intelligent terminal APP application analysis, intelligent detection of university students' health status, attention mechanism, gated recurrent unit neural network, intelligent optimisation algorithm

Abstract

As a carrier of college students' health status monitoring, portable intelligent terminal APP, the study of its APP application analysis not only provides a new way for college students' extracurricular physical exercise, guides college students to actively participate in extracurricular physical activities using intelligent terminal APP software, but also promotes college students' physical health monitoring and enhancement in various aspects. Aiming at the current portable terminal APP college students' health monitoring application analysis method research exists low precision, real-time poor and other problems, through the analysis of the basic functional framework and functional characteristics of the portable intelligent terminal APP, the establishment of the portable intelligent terminal APP analysis index system applied to college students' health monitoring, combined with the heuristic optimisation algorithm and the improvement of deep learning algorithms, the construction of the marine predator based heuristic optimisation algorithm and the attention mechanism to improve the gating control loop. Combining the heuristic optimisation algorithm and the improved deep learning algorithm, we construct the portable intelligent terminal APP application analysis method for college students' health monitoring based on the marine predator heuristic optimisation algorithm and the attention mechanism improved gated recurrent unit neural network. Through simulation analysis, the results show that the proposed method meets the real-time requirements while improving the prediction accuracy of the portable smart terminal APP application analysis method, and significantly improves the efficiency of portable smart terminal APP analysis.

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