Search results for: Hewen Li

Authors: Yilin Liao, Hewen Li, Paula McConvey

Abstract:

Concussion for speed skaters often occurs when skaters fall on the ice and impact the crash mats during practices and competition races. Gaining insight into the impact of interactions is of essential interest as it is directly related to skaters’ potential health risks and injuries. Precise concussion measurements are challenging and very difficult, making computer simulation the only reliable way to analyze accidents. This research aims to create the crash mat and skater’s multi-body model using Solidworks, develop a computer simulation model for skater-mat impact using ANSYS software, and predict the skater’s concussion degree by evaluating the “head injury criteria” (HIC) through the resulting accelerations. The developed method and results help understand the relationship between impact parameters and concussion risk for speed skaters and inform the design of crash mats and skating rink layouts more specifically by considering athletes’ health risks.

Keywords: computer simulation modeling, concussion, impact, speed skater

Procedia PDF Downloads 104

Authors: Yilin Liao, Hewen Li, Paula McConvey

Abstract:

Speed skaters often face a risk of concussion when they fall on the ice floor and impact crash mats during practices and competitive races. Several variables, including those related to the skater, the crash mat, and the impact position (body side/head/feet impact), are believed to influence the severity of the skater's concussion. While computer simulation modeling can be employed to analyze these accidents, the simulation process is time-consuming and does not provide rapid information for coaches and teams to assess the skater's injury risk in competitive events. This research paper promotes the exploration of the feasibility of using AI techniques for evaluating skater’s potential concussion severity, and to develop a fast concussion prediction tool using artificial neural networks to reduce the risk of treatment delays for injured skaters. The primary data is collected through virtual tests and physical experiments designed to simulate skater-mat impact. It is then analyzed to identify patterns and correlations; finally, it is used to train and fine-tune the artificial neural networks for accurate prediction. The development of the prediction tool by employing machine learning strategies contributes to the application of AI methods in sports science and has theoretical involvements for using AI techniques in predicting and preventing sports-related injuries.

Keywords: artificial neural networks, concussion, machine learning, impact, speed skater

Procedia PDF Downloads 64