Biomechanical model-based displacement estimation in micro-sensor motion capture

Abstract

In micro-sensor motion capture systems, the estimation of the body displacement in the global coordinate system remains a challenge due to lack of external references. This paper proposes a self-contained displacement estimation method based on a human biomechanical model to track the position of walking subjects in the global coordinate system without any additional supporting infrastructures. The proposed approach makes use of the biomechanics of the lower body segments and the assumption that during walking there is always at least one foot in contact with the ground. The ground contact joint is detected based on walking gait characteristics and used as the external references of the human body. The relative positions of the other joints are obtained from hierarchical transformations based on the biomechanical model. Anatomical constraints are proposed to apply to some specific joints of the lower body to further improve the accuracy of the algorithm. Performance of the proposed algorithm is compared with an optical motion capture system. The method is also demonstrated in outdoor and indoor long distance walking scenarios. The experimental results demonstrate clearly that the biomechanical model improves the displacement accuracy within the proposed framework.