The eigenmode analysis of human motion

Abstract

Rapid advances in modern communication technology are enabling the accumulation of large-scale, high-resolution observational data of the spatiotemporal movements of humans. Classification and prediction of human mobility based on the analysis of such data has great potential in applications such as urban planning in addition to being a subject of theoretical interest. A robust theoretical framework is therefore required to study and properly understand human motion. Here we perform the eigenmode analysis of human motion data gathered from mobile communication records, which allows us to explore the scaling properties and characteristics of human motion.