Statistical Extraction Method for Revealing Key Factors from Posture before Initiating Successful Throwing Technique in Judo

1. Research background

Recent modern training is based on observing target movements from videos. The trend is considered as one of the most important training methods to let the learners understand their own movements. However, these training methods have the problem that due to one’s subjectivity and coach’s biased interpretation by the diversity of a player’s physical characteristics and their condition, it cannot be standardized. Therefore, to eliminate this problem, methods to measure skills objectively by using inertial sensors have been researched. However, these conventional methods do not consider the external force on the motor subject, and focus on the individual’s motor ability. there exists a problem that these methods are not applicable to combat sports such as judo, wrestling, boxing etc. These combat sports include interactions between players.
This research project proposes a novel method that derives key factors for effective learning of a movement in combat sports. We will focus on judo as a high-impact example of combat sports and propose a method to derive the key factors for successful throwing techniques. In this research project, we will focus on postures before successful throwing techniques. Then, we propose a statistical method. The method will derive the key factors that induce successful throwing techniques from the posture right before the throwing techniques.

2. Research outcomes

We select as many candidate factors of a successful throwing as possible from the throw（called Tori） positions and the throwee（called Uke）positions. We also define the types of throwing techniques as the successful movements and the candidate actions that lead to a successful throw as the candidate factors. And We obtain datasets that contains the types of successful movements, candidate factors and attributes, and analyze the datasets from the video database.
Then, we analyzes the correlations among the successful movements and the candidate factors by χ2 test. By this analyzing, we can find the successful factors from the candidate factors.
As a dataset of the scenes that include the throwing techniques, we will use the video database recorded in the World Judo Championships available from the IJF website. We collected 781 successful scenes of single throwing techniques except counter and combinational ones. By the XSM method analysis for the dataset, we find the successful factors from postures before initiating a successful movement. And we find differences among groups by projecting a subset of the dataset against attributes (gender difference, weight class, etc.).