Nonlinear modelling and control for heart rate response to exercise.
In order to accurately regulate cardiovascular response to exercise for individual exerciser, this study proposes a modelling and control integrated approach based on ε-insensitive Support Vector Regression (SVR) and switching control strategy. Firstly, a control oriented modelling approach is proposed to depict nonlinear behaviours of cardiovascular response at both onset and offset of treadmill exercises by using support vector machine regression. Then, based on the established nonlinear time-variant model, a novel switching Model Predictive Control (MPC) algorithm has been proposed for the optimisation of exercise efforts. The designed controller can take into account both coefficient drifting and parameter jump by embedding the identified model coefficient into the optimiser and adopting switching strategy during the transfer between onset and offset of exercises. The effectiveness of the proposed modelling and control approach was shown from the regulation of dynamical heart rate response to exercise through simulation using MATLAB.
Centre for Health Technologies, University of Technology, Sydney, Australia.
Y
Y
Zhang
W
W
Chen
S W
SW
Su
B
B
Celler
D015444:Exercise / Q000502:physiology*; D005080:Exercise Test; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D017711:Nonlinear Dynamics; D016138:Walking / Q000502:physiology