A multi-step heart rate prediction method based on physical activity using Adams-Bashforth technique

  • Authors:

  • Feng Xiao;Ming Yuchi;Ming-yue Ding;Jun Jo;Jong-Hwan Kim

  • Affiliations:

  • Faculty of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China;Faculty of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China;Faculty of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China;School of Information and Communication Technology, Griffith University, Queensland, Australia;Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea

  • Venue:
  • CIRA'09 Proceedings of the 8th IEEE international conference on Computational intelligence in robotics and automation
  • Year:
  • 2009

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Abstract

Physical activity (PA) is commonly recognized to directly influence changes in heart rate (HR). HR prediction based on PA can be a useful tool in medical research and monitoring in a clinical setting. In our previous works, predictors with high accuracy were designed. However, the HR could only be predicted in single time steps. In this study, a multi-step HR prediction method is proposed. Firstly, the HR prediction problem was converted into an Initial-Value Problem for Ordinary Differential Equation (IVPODE). Then the Adams-Bashforth method was used to implement multistep prediction. Only HR at the initial time step and PA signals are needed. Experiments were conducted based on the real-life signals from a healthy male. Predicted HR can approximately trace the actual HR in a long time step. The results show the potential of this proposed method.