A Method to Analyze Human's Behavior using Singular Value Decomposition for Motion Teaching

Abstract

Human can master various motions from training. It usually takes a lot of time and cost. It is well-known that teaching is useful in mastering motions. However, most of teachings tend to teach depending on coach's subjectivity or experiences. The purpose of our research is to establish a method to analyze human's behavior using singular value decomposition and for motion teaching based on its results. Behavior changes through the training, so that motion change point arrays extracted using singular spectrum transformation differ from proficiency. In this paper, a method to identify difference of change point arrays extracted using singular spectrum transformation. Experimental results in mastering and teaching throwing of lacrosse shows the effectiveness of the proposed method.