Design of College Students' physical health monitoring APP based on sports health big data

被引:1
作者
Zhang, Xiaoni [1 ]
Li, Ran [1 ]
Li, Yunwei [1 ]
Wang, Yunsheng [2 ]
Wu, Feilong [1 ,3 ,4 ]
机构
[1] Xian Aeronaut Univ, Dept Phys Educ, Xian, Peoples R China
[2] Xian Siyuan Univ, Xian, Peoples R China
[3] Jose Rizal Univ, Grad Sch, Mandaluyong, Philippines
[4] Xian Aeronaut Univ, Dept Phys Educ, Xian 710077, Shaanxi, Peoples R China
关键词
college Students' physical health monitoring; data mining; health monitoring APP design; intelligent medical; sports health big data; INTERNET; THINGS;
D O I
10.1002/itl2.432
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
At present, the living habits of college students are relatively poor, and the amount of exercise is reduced, leading to their physical fitness getting worse and worse. Therefore, people began to study the physical health monitoring of college students. Machine learning and high-performance computing in medical applications provide technical support for intelligent medical technology. With the rapid development of computer network, human beings have entered the information and digital era, and sports health big data has become more and more popular. The combination of sports health big data and student physical health monitoring technology, in a sense, can realize automatic data processing through intelligent medical and sports health database and other information technologies, thus promoting the popularization of health monitoring technology. However, the current health monitoring equipment has many problems, such as complex collection, low accuracy and limited processing of health data. To solve this problem, this paper developed an Application (APP) based on sports health big data technology that can monitor multiple vital signs such as human heart rate and body temperature, and analyze the physical health of college students, so that college students can easily understand their health status in daily life, so as to promote the healthy development of students' physique and encourage them to actively participate in physical exercise. The experiment proved that, in the heart rate monitoring, when the speed is 6 km/h, the error rate of the college students' physical health monitoring APP designed in this paper is 8.15%. The average accuracy rate of student steps monitoring is 97.12%. This showed the accuracy and availability of the APP's monitoring function for human vital signs. It has certain application value and significance to help students improve their physical quality.
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页数:6
相关论文
共 12 条
  • [1] Wearable and flexible sensors for user-interactive health-monitoring devices
    Ha, Minjeong
    Lim, Seongdong
    Ko, Hyunhyub
    [J]. JOURNAL OF MATERIALS CHEMISTRY B, 2018, 6 (24) : 4043 - 4064
  • [2] Hurley D., 2021, AM J MED RES, V8, P78, DOI [10.22381/ajmr8220216, DOI 10.22381/AJMR8220216]
  • [3] Based Real Time Remote Health Monitoring Systems: A Review on Patients Prioritization and Related "Big Data" Using Body Sensors information and Communication Technology
    Kalid, Naser
    Zaidan, A. A.
    Zaidan, B. B.
    Salman, Omar H.
    Hashim, M.
    Muzammil, H.
    [J]. JOURNAL OF MEDICAL SYSTEMS, 2018, 42 (02)
  • [4] A Wireless Health Monitoring System Using Mobile Phone Accessories
    Mahmud, Md. Shaad
    Wang, Honggang
    Esfar-E-Alam, A. M.
    Fang, Hua
    [J]. IEEE INTERNET OF THINGS JOURNAL, 2017, 4 (06): : 2009 - 2018
  • [5] Automated Health Monitoring System Using Advanced Technology
    Muneer, Amgad
    Fati, Suliman Mohamed
    [J]. JOURNAL OF INFORMATION TECHNOLOGY RESEARCH, 2019, 12 (03) : 104 - 132
  • [6] Rahaman Ashikur, 2019, Revue d'Intelligence Artificielle, V33, P435, DOI 10.18280/ria.330605
  • [7] Monitoring and Evaluating College Students' Mental Health Based on Big Data Analysis
    Shi, Qiuxiang
    Cai, Ning
    Jiao, Weiting
    [J]. AMERICAN JOURNAL OF HEALTH BEHAVIOR, 2022, 46 (02): : 164 - 176
  • [8] Singh P., 2018, International Journal of Advanced Research in Computer Science, V9, P224, DOI [10.26483/ijarcs.v9i1.5308, DOI 10.26483/IJARCS.V9I1.5308]
  • [9] Internet of Things-assisted intelligent monitoring model to analyze the physical health condition
    Tang, Xiaowei
    Li, Fang
    Seetharam, Tamizharasi G.
    Vignesh, C. Chandru
    [J]. TECHNOLOGY AND HEALTH CARE, 2021, 29 (06) : 1355 - 1369
  • [10] Structural Health Monitoring Framework Based on Internet of Things: A Survey
    Tokognon, C. Jr. Arcadius
    Gao, Bin
    Tian, Gui Yun
    Yan, Yan
    [J]. IEEE INTERNET OF THINGS JOURNAL, 2017, 4 (03): : 619 - 635