Dynamic Systems Theory in Human Movement Exploring Coordination Patterns by Angle-Angle Diagrams Using Kinect

Abstract

Analyzing time series data using linear spatial/angular kinematics traditionally makes quantification of human movement using low-cost cameras such as the Kinect sensor. Through this conventional approach, interactions between body joints are difficult to analyze and coordination parameters remain hidden. Dynamic Systems Theory (DST) provides a non-linear framework to analyze human movement by representing intersegmental interactions in angle-angle diagrams. DST offers an accurate solution to study coordination in human movement, but it also requires expensive hardware and very specialized biomechanical software. The paper describes a methodological procedure to carry out DST analysis with motion data recorded from the Kinect sensor. Specifically, we address the issue to create and interpret angle-angle diagrams with an emphasis on exploring coordination patterns in motion capture (MoCap) signals. We introduced a method to facilitate the DST analysis and we applied it with two different use cases of human movement analysis in real scenarios: sports gesture study and motion analysis in physical rehabilitation interventions. Results showed that important coordination parameters could be deduced from the angle-angle diagrams improving the understanding of motion data when two joints have to be considered. Therefore, we demonstrated that DST analysis could be performed with inexpensive tools providing a promissory approach for coordination and motor synchronization analysis in novel serious games for health.