Comparative study of segmentation of periodic motion data for mobile gait analysis

Abstract

Two approaches are presented and compared for segmenting motion data from on-body Orient wireless motion capture system for mobile gait analysis. The first is a basic, model-based algorithm which operates directly on the joint angles computed by the Orient sensor devices. The second is a model-free, Latent Space algorithm, which first aggregates all the sensor data, and then embeds them in a low-dimensional manifold to perform segmentation. The two approaches are compared for segmenting four different styles of walking, and then applied in a hospital-based clinical study for analysing the motion of elderly patients recovering from a fall.