Management and Analysis of Sports Health Level of the Elderly Based on Deep Learning

被引:0
|
作者
Xiao, Liping [1 ]
Huang, Limin [2 ]
Chang, Hongxia [1 ]
Ji, Li [3 ]
Li, Ji [1 ]
机构
[1] Harbin Normal Univ, Coll Sports Sci, Harbin 150025, Peoples R China
[2] Harbin Sport Univ, Coll Sports & Human Sci, Harbin 150008, Peoples R China
[3] Adm Sport Persons Disabil, Beijing 101318, Peoples R China
关键词
DECISION-SUPPORT; INDEX; MOBILE;
D O I
10.1155/2022/6044320
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
With the accelerating rate of population aging in China, the health of the elderly has received more and more attention and has become one of the most important issues in the elderly care industry. Because of insufficient research on the personal health of the elderly, the value of medical examination data cannot be fully exploited, many physical indicators have a certain impact on overall health or heart health, and there are few studies on heart health assessment. This paper proposes a deep learning-based elderly management analysis method of human exercise health level, using the exercise health management model to evaluate the heart health level of the elderly. Firstly, the indicators to measure heart health are proposed through traditional expert knowledge and personal health index to analyze heart health. Through dynamic assessment, predict the heart health status at the next time point, analyze possible heart diseases, and provide corresponding methods for the health of the elderly, which helps improve the physical health of the elderly. Quality of life provides assistance to meet the needs of improving the health of older adults.
引用
收藏
页数:8
相关论文
共 50 条
  • [41] A Sports Training Video Classification Model Based on Deep Learning
    Xu, Yunjun
    [J]. SCIENTIFIC PROGRAMMING, 2021, 2021
  • [42] Multimodal deep learning based on multiple correspondence analysis for disaster management
    Samira Pouyanfar
    Yudong Tao
    Haiman Tian
    Shu-Ching Chen
    Mei-Ling Shyu
    [J]. World Wide Web, 2019, 22 : 1893 - 1911
  • [43] Multimodal deep learning based on multiple correspondence analysis for disaster management
    Pouyanfar, Samira
    Tao, Yudong
    Tian, Haiman
    Chen, Shu-Ching
    Shyu, Mei-Ling
    [J]. WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS, 2019, 22 (05): : 1893 - 1911
  • [44] Deep Learning based Crack Growth Analysis for Structural Health Monitoring
    Chambon, A.
    Bellaouchou, A.
    Atamuradov, V
    Vitillo, F.
    Plana, R.
    [J]. IFAC PAPERSONLINE, 2022, 55 (10): : 3268 - 3273
  • [45] An automated deep learning based satellite imagery analysis for ecology management
    Alshahrani, Haya Mesfer
    Al-Wesabi, Fahd N.
    Al Duhayyim, Mesfer
    Nemri, Nadhem
    Kadry, Seifedine
    Alqaralleh, Bassam A. Y.
    [J]. ECOLOGICAL INFORMATICS, 2021, 66
  • [46] RETRACTED: Deep Learning-Based Detection and Identification Method for Sports Health Video Dissemination (Retracted Article)
    Pang, Yajun
    [J]. DISCRETE DYNAMICS IN NATURE AND SOCIETY, 2022, 2022
  • [47] RETRACTED: Research on Sports Health Care Information System Based on Computer Deep Learning Algorithm (Retracted Article)
    Ma, Xiaojun
    Zhang, Zhenfeng
    [J]. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2022, 2022
  • [48] A Review on Deep Learning Applications in Prognostics and Health Management
    Zhang, Liangwei
    Lin, Jing
    Liu, Bin
    Zhang, Zhicong
    Yan, Xiaohui
    Wei, Muheng
    [J]. IEEE ACCESS, 2019, 7 : 162415 - 162438
  • [49] Application of deep learning in equipment prognostics and health management
    Chen, Zhiqiang
    Chen, Xudong
    De Olivira, José Valente
    Li, Chuan
    [J]. Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument, 2019, 40 (09): : 206 - 226
  • [50] A review on the application of deep learning in system health management
    Khan, Samir
    Yairi, Takehisa
    [J]. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2018, 107 : 241 - 265