Development of automatic positioning system for bicycle saddle based on lower limb's EMG signals during pedaling motion

Abstract

This paper proposes an automation system for cyclists, which provides the optimum setting of bicycle components such as saddle and handle against the physical properties of a cyclist. In order to complete our purpose, the evaluation criteria for saddle setting by using bio-signals of a cyclist who pedals a bicycle have to be established firstly. We focus on patterns of muscle activity of the leg muscles that activate in pedaling exercise, and assume that undesirable pattern of muscle activity would appear in the pedaling motion of inexperienced cyclists. We use principal component analysis (PCA) to extract the features of muscle activity from the leg muscles. Our previous work has already clarified that the PCA scores come close to zero in the pedaling motion performed by a skilled cyclist at the saddle height which is subjectively evaluated good. In this paper, we add other degrees of freedoms of saddle setting such as fore-and-back position and angle adjustment to the experimental device. Surface electromyogram (SEMG) of the leg muscles has also been used to measure bio-signals of a cyclist during pedaling exercise. With the use of the aforementioned experimental environment, the effects of setting height and fore-and-back position to the pattern of muscle activity of the leg muscles are investigated in this paper.