• DocumentCode
    2539168
  • Title

    Heart Rate Prediction Model Based on Physical Activities Using Evolutionary Neural Network

  • Author

    Xiao, Feng ; Chen, Yi-min ; Yuchi, Ming ; Ding, Ming-yue ; Jo, Jun

  • Author_Institution
    Life Coll. of Sci. & Technol., Huazhong Univ. of Sci. & Technol., Wuhan, China
  • fYear
    2010
  • fDate
    13-15 Dec. 2010
  • Firstpage
    198
  • Lastpage
    201
  • Abstract
    Physical activity (PA) can influence heart rate(HR). But the relationship between HR and PA is hard to describe. In our previous works, HR prediction models based on PA were designed. However, the prediction time length and accuracy are usually hard to compromise. In this study, a new HR prediction method is proposed. The predicted HR is used as the input in the next prediction step. Only HR at the initial time step and PA signals are needed in a long prediction time length. Evolutionary neural network is used as the mathematic basic of the predictor to ensure the prediction accuracy. The results show the predicted HR can trace the actual HR well.
  • Keywords
    cardiology; medical signal processing; neural nets; prediction theory; ECG signal; PA signal; evolutionary neural network; heart rate prediction model; heart rate signal analysis; multistep prediction; physical activity; Accuracy; Artificial neural networks; Biomedical monitoring; Heart rate; Monitoring; Predictive models; Training; Evolutionary Neural Network; Heart Rate; Multi-Step Prediction; Physical Activity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Genetic and Evolutionary Computing (ICGEC), 2010 Fourth International Conference on
  • Conference_Location
    Shenzhen
  • Print_ISBN
    978-1-4244-8891-9
  • Electronic_ISBN
    978-0-7695-4281-2
  • Type

    conf

  • DOI
    10.1109/ICGEC.2010.56
  • Filename
    5715404