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A fitness training optimization system based on heart rate prediction under different activities.

Publication ,  Journal Article
Zhu, Z; Li, H; Xiao, J; Xu, W; Huang, M-C
Published in: Methods (San Diego, Calif.)
September 2022

Heart rate can be considered as an indicator of the exercise intensity in people's daily physical activities. Five heart rate zone theory is commonly adopted by individuals and professional athletes during their exercises and training. These heart rate zones are based upon percentages of people's maximal heart rate, which indicate different exercise intensities. The aim of paper is to propose an optimization training system based on dynamic heart rate prediction, which can predict people's heart rate under three different types of exercises: walking, running and rope jumping. The system can help people optimize their exercise by advising them to adjust the speed or workload to reach their predetermined training intensity under different activities. Four Long Short-Term Memory (LSTM) neural networks are deployed, one for human activity recognition (HAR) and three for heart rate prediction.

Duke Scholars

Published In

Methods (San Diego, Calif.)

DOI

EISSN

1095-9130

ISSN

1046-2023

Publication Date

September 2022

Volume

205

Start / End Page

89 / 96

Related Subject Headings

  • Walking
  • Running
  • Physical Fitness
  • Neural Networks, Computer
  • Humans
  • Heart Rate
  • Exercise
  • 3101 Biochemistry and cell biology
  • 1103 Clinical Sciences
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Zhu, Z., Li, H., Xiao, J., Xu, W., & Huang, M.-C. (2022). A fitness training optimization system based on heart rate prediction under different activities. Methods (San Diego, Calif.), 205, 89–96. https://doi.org/10.1016/j.ymeth.2022.06.006
Zhu, Zetao, Huining Li, Jian Xiao, Wenyao Xu, and Ming-Chun Huang. “A fitness training optimization system based on heart rate prediction under different activities.Methods (San Diego, Calif.) 205 (September 2022): 89–96. https://doi.org/10.1016/j.ymeth.2022.06.006.
Zhu Z, Li H, Xiao J, Xu W, Huang M-C. A fitness training optimization system based on heart rate prediction under different activities. Methods (San Diego, Calif). 2022 Sep;205:89–96.
Zhu, Zetao, et al. “A fitness training optimization system based on heart rate prediction under different activities.Methods (San Diego, Calif.), vol. 205, Sept. 2022, pp. 89–96. Epmc, doi:10.1016/j.ymeth.2022.06.006.
Zhu Z, Li H, Xiao J, Xu W, Huang M-C. A fitness training optimization system based on heart rate prediction under different activities. Methods (San Diego, Calif). 2022 Sep;205:89–96.
Journal cover image

Published In

Methods (San Diego, Calif.)

DOI

EISSN

1095-9130

ISSN

1046-2023

Publication Date

September 2022

Volume

205

Start / End Page

89 / 96

Related Subject Headings

  • Walking
  • Running
  • Physical Fitness
  • Neural Networks, Computer
  • Humans
  • Heart Rate
  • Exercise
  • 3101 Biochemistry and cell biology
  • 1103 Clinical Sciences