Exploring Cognitive and Perceptual Judgment Processes in Gymnastics Using Essential Kinematics Information

Action Quality Assessment Model Using Specialists' Gaze Location and Kinematics Data-Focusing on Evaluating Figure Skating Jumps

Action quality assessment (AQA) tasks in computer vision evaluate action quality in videos, and they can be applied to sports for performance evaluation. A typical example of AQA is predicting the final score from a video that captures an entire figure skating program. However, no previous studies have predicted individual jump scores, which are of great interest to competitors because of the high weight of competition. Despite the presence of unnecessary information in figure skating videos, human specialists can focus and reduce information when they evaluate jumps. In this study, we clarified the eye movements of figure skating judges and skaters while evaluating jumps and proposed a prediction model for jump performance that utilized specialists' gaze location to reduce information. Kinematic features obtained from the tracking system were input into the model in addition to videos to improve accuracy. The results showed that skaters focused more on the face, whereas judges focused on the lower extremities. These gaze locations were applied to the model, which demonstrated the highest accuracy when utilizing both specialists' gaze locations. The model outperformed human predictions and the baseline model (RMSE:0.775), suggesting a combination of human specialist knowledge and machine capabilities could yield higher accuracy.

Kinematic analysis as the basis for training strategy in gymnastics

The kinematic analysis of gymnastic skills performance is a widely used research method in sports science. This study presents the experience of applying the method of kinematic analysis in the managing the training process of junior gymnasts on the example of mastering three basic gymnastic skills. The test group included 10 junior male gymnasts of the age 9 to 12. The subject of kinematic analysis was based on comparing gymnasts’ joint angles, angular velocity and angular acceleration parameters. The kinematics parameters of gymnastic skills performance by a highly qualified gymnast became the target model for junior gymnasts. As a result of these targets application in the training of junior gymnasts, changes in the basic skills kinematic parameters were detected. At the end of the study, the kinematics parameters of junior gymnasts became much closer to the model parameters. Thus, the effectiveness of the kinematics analysis method in the training of junior gymnasts was demonstrated.