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Author:

Su, Jun (Su, Jun.) | Zhang, Song (Zhang, Song.) | Yang, Lin (Yang, Lin.) | Li, Xiao-he (Li, Xiao-he.)

Indexed by:

CPCI-SSH

Abstract:

In recent years, with a gradual decline of teenagers' fitness and health monitoring data in our country, physical health of teenagers is becoming a more and more important problem. The traditional evaluation method can test teenagers' health condition by spot checks every year. However it is difficult to analyze the changes of the teenagers' physical data. In the present paper, an early warning system of physical exercise based on exercise heart rate and time is proposed. The system classifies the intensity of movement by exercise heart rate and time, and then calculates the load and the score according to the evaluation standards we put. To verify the maneuverability of the evaluation theory model, real-time monitoring of heart rate during physical education class in a high school is conducted. Results show that based on exercise heart rate and time, the score of teenagers' exercise condition can be obtained, which can reflect the daily exercise of each person intuitively.

Keyword:

Early warning system Exercise heart rate Fitness and health monitoring

Author Community:

  • [ 1 ] [Su, Jun]Beijing Univ Technol, Coll Life Sci & Bioengn, Beijing 100124, Peoples R China
  • [ 2 ] [Zhang, Song]Beijing Univ Technol, Coll Life Sci & Bioengn, Beijing 100124, Peoples R China
  • [ 3 ] [Yang, Lin]Beijing Univ Technol, Coll Life Sci & Bioengn, Beijing 100124, Peoples R China
  • [ 4 ] [Su, Jun]Beijing Municipal Bur Sports, Youth Sports Dept, Beijing 100075, Peoples R China
  • [ 5 ] [Li, Xiao-he]ZhongShiHongLi Beijing Hlth Technol Co Ltd, Beijing, Peoples R China

Reprint Author's Address:

  • [Yang, Lin]Beijing Univ Technol, Coll Life Sci & Bioengn, Beijing 100124, Peoples R China

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Source :

PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON HUMANITIES AND SOCIAL SCIENCE (HSS 2016)

ISSN: 2352-5398

Year: 2016

Volume: 33

Page: 755-758

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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