Abstract
Walking difficulty often happens in times of disasters. Identification of the evacuees with walking difficulty will definitely lead to quick rescue and thus improve the efficiency of evacuation. A precise and convenient method is being developed to automatically analyze the evacuees' walking. In this paper, we propose a method for assessing walking difficulty using singular value analysis through divided time-series data (SVA-DTS). In order to verify the usefulness of the proposed method, three levels of walking difficulty in the lower limbs are simulated in an experiment by constraining the knee joint and ankle joint of the right leg. The accelerations of the middle of shanks and the back of the waist are measured. The results showed that the first singular values inferred from the acceleration data of the right shank significantly related to the increase of the constraint to the joints. The first singular values of the acceleration data of the shanks were suggested to be reliable criteria to evaluate walking difficulty. We visualize the first singular values in a 3D space to provide intuitive information about walking ability which can be used as a tool for identifying the evacuees with walking difficulty.
