AN INTELLIGENT TREADMILL SYSTEM FOR RUNNING TRAINING: CONTROL OF BELT SPEED AND BIOFEEDBACK

Abstract

We developed an intelligent treadmill system to realize more comfortable and safer running exercise. In the first part, we developed an algorithm to estimate the intended running speed of the user. We used the relation between the forward impulse of ground reaction force during the stance phase, stance time and swing time to estimate the intended running speed. We implemented the algorithm to an instrumented treadmill. In the second part, we evaluated the effects of real-time biofeedback of the mechanical stress on the legs. Initial peak of ground reaction force and leg stiffness value calculated based on the mass-spring model was visually shown. The subjects were instructed to reduce these values. It was found that initial peak of ground reaction force as well as leg stiffness can be effectively adjusted using visual biofeedback.