Sports health monitoring management system based on artificial intelligence algorithm
With the improvement of people's material living standards, more and more people start to pay attention to health issues. This paper takes the health field as the main research object, and discusses the current development and status quo of the health field. Through literature review, it is fou...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-03-01
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| Series: | Frontiers in Physics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fphy.2023.1141944/full |
| _version_ | 1811158935015522304 |
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| author | Yunlong Tong Lina Ye |
| author_facet | Yunlong Tong Lina Ye |
| author_sort | Yunlong Tong |
| collection | DOAJ |
| description | With the improvement of people's material living standards, more and more people start to pay attention to health issues. This paper takes the health field as the main research object, and discusses the current development and status quo of the health field. Through literature review, it is found that the current health field mainly focuses on the single monitoring of a certain organ or body function, and there are limitations in systematic health monitoring research, and most of the research stays at the stage of human body monitoring. Therefore, this paper intends to design a sports health monitoring and management system based on artificial intelligence. The system is mainly divided into a body temperature monitoring module, a blood pressure monitoring module and an exercise monitoring module, through which the user's health data is monitored. In order to ensure the practicability of the system, this paper selects three common life states in daily life for experimental testing, namely exercise state, rest state and sick state. The experimental test results show that each monitoring module can operate correctly and normally under three different states. The lowest temperature was 36.5° and the highest temperature was 37.1° under the exercise state. The lowest blood pressure is 70 in the resting state, and the highest blood pressure is 80. In the sick state, the maximum value of motor threshold is 0.2, the minimum value is 0.1, and the threshold difference is 0.1. Each module reads and backs up relevant data, and sends it to the platform for intelligent analysis. The platform will analyze and compare the data of different modules at the same time, judge the health status of the user at that time, choose whether to issue a health alert for the user, and finally complete the entire system process of the health monitoring management system. This proves that the sports health monitoring management system based on artificial intelligence algorithm designed in this paper is effective and feasible. |
| first_indexed | 2024-04-10T05:32:43Z |
| format | Article |
| id | doaj.art-c0aab3bcd4904c9d98924a29e24e776d |
| institution | Directory Open Access Journal |
| issn | 2296-424X |
| language | English |
| last_indexed | 2024-04-10T05:32:43Z |
| publishDate | 2023-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Physics |
| spelling | doaj.art-c0aab3bcd4904c9d98924a29e24e776d2023-03-07T05:53:26ZengFrontiers Media S.A.Frontiers in Physics2296-424X2023-03-011110.3389/fphy.2023.11419441141944Sports health monitoring management system based on artificial intelligence algorithmYunlong Tong0Lina Ye1Institute of Physical Education, Jilin Normal University, Siping, ChinaCollege of Mathematics and Computer, Jilin Normal University, Siping, ChinaWith the improvement of people's material living standards, more and more people start to pay attention to health issues. This paper takes the health field as the main research object, and discusses the current development and status quo of the health field. Through literature review, it is found that the current health field mainly focuses on the single monitoring of a certain organ or body function, and there are limitations in systematic health monitoring research, and most of the research stays at the stage of human body monitoring. Therefore, this paper intends to design a sports health monitoring and management system based on artificial intelligence. The system is mainly divided into a body temperature monitoring module, a blood pressure monitoring module and an exercise monitoring module, through which the user's health data is monitored. In order to ensure the practicability of the system, this paper selects three common life states in daily life for experimental testing, namely exercise state, rest state and sick state. The experimental test results show that each monitoring module can operate correctly and normally under three different states. The lowest temperature was 36.5° and the highest temperature was 37.1° under the exercise state. The lowest blood pressure is 70 in the resting state, and the highest blood pressure is 80. In the sick state, the maximum value of motor threshold is 0.2, the minimum value is 0.1, and the threshold difference is 0.1. Each module reads and backs up relevant data, and sends it to the platform for intelligent analysis. The platform will analyze and compare the data of different modules at the same time, judge the health status of the user at that time, choose whether to issue a health alert for the user, and finally complete the entire system process of the health monitoring management system. This proves that the sports health monitoring management system based on artificial intelligence algorithm designed in this paper is effective and feasible.https://www.frontiersin.org/articles/10.3389/fphy.2023.1141944/fullsports health monitoring and management systemartificial intelligence algorithmsbody temperature monitoringmonitoring of blood pressureartificial intelligence |
| spellingShingle | Yunlong Tong Lina Ye Sports health monitoring management system based on artificial intelligence algorithm Frontiers in Physics sports health monitoring and management system artificial intelligence algorithms body temperature monitoring monitoring of blood pressure artificial intelligence |
| title | Sports health monitoring management system based on artificial intelligence algorithm |
| title_full | Sports health monitoring management system based on artificial intelligence algorithm |
| title_fullStr | Sports health monitoring management system based on artificial intelligence algorithm |
| title_full_unstemmed | Sports health monitoring management system based on artificial intelligence algorithm |
| title_short | Sports health monitoring management system based on artificial intelligence algorithm |
| title_sort | sports health monitoring management system based on artificial intelligence algorithm |
| topic | sports health monitoring and management system artificial intelligence algorithms body temperature monitoring monitoring of blood pressure artificial intelligence |
| url | https://www.frontiersin.org/articles/10.3389/fphy.2023.1141944/full |
| work_keys_str_mv | AT yunlongtong sportshealthmonitoringmanagementsystembasedonartificialintelligencealgorithm AT linaye sportshealthmonitoringmanagementsystembasedonartificialintelligencealgorithm |