Extraction of Coordinative Structures of Motions by Segmentation Using Singular Spectrum Transformation

In this article, we focus on the coordinative structure of human behavior, which contributes to specifying dynamics from time-series kinematic data. We propose a method for the extraction of dynamical interaction from time-series data of human behavior using Singular Spectrum Transformation. Using the proposed method, human behavior can be described as a letter string whose letters indicate where the motion segmentation is detected. We also discuss a method of extracting coordinative structures by constructing multiple alignments from the timing structure of extracted motion change points. To confirm the effectivity of the proposed method, the results of motion analysis are shown.