Modelling and control for heart rate regulation during treadmill exercise.

This paper proposes a novel integrated approach for the identification and control of Hammerstein systems to achieve desired heart rate tracking performance for an automated treadmill system. The pseudo-random binary sequence input is employed to decouple the identification of dynamic linear part from static nonlinearity. The powerful e-insensitivity support vector regression is adopted to obtain sparse representations of the inversion of static nonlinearity in order to obtain an approximated linear model of the Hammerstein system. An H(infinity) controller is designed for the approximated linear model to achieve robust tracking performance. This new approach is applied to the design of a computer-controlled treadmill system for the regulation of heart rate during treadmill exercise. Minimizing deviations of heart rate from a preset profile is achieved by controlling the speed of the treadmill. Both conventional proportional-integral-derivative (PID) control and the proposed approaches have been employed for the controller design. The proposed algorithm achieves much better heart rate tracking performance.