Abstract
ABSTRACT Introduction: With the continuous development of society and the continuous improvement of the economic level, the willingness of Chinese people to participate in sports is also showing an upward trend. However, how to reduce sports damage as much as possible during exercise should be a hot issue of particular concern to athletes in the sports world. Objective: It aimed to discuss the simulation of the relationship between joint motion amplitude (JMA) and motion damage (MD) via a rough set decision-making algorithm to avoid MD. Based on the rough set decision algorithm, JMA and MD models were constructed, and a motion data decision table was established. Methods: Joint change parameters and constraint conditions were set, and joint change parameters were analyzed. Moreover, the changing parameters, feature strength, and algorithm partition accuracy of the simulation model were analyzed. Results: The feature strength and the division accuracy of the rough set decision algorithm all showed good accuracy. The model constructed by such a method can well describe the relationship between JMA and MD. Conclusion: The proposed rough set decision algorithm can describe the relationship between JMA and MD scientifically and effectively, which provided reference value for sports. Level of evidence II; Therapeutic studies - investigation of treatment results.
Highlights
With the continuous development of society and the continuous improvement of the economic level, the willingness of Chinese people to participate in sports is showing an upward trend
Two identical unobstructed motion camera capture points in each dotted frame were selected, and the rigid body was recorded in detail
It is hoped that the research in this article can help to well alleviate the damage caused by the excessive joint motion amplitude (JMA)
Summary
With the continuous development of society and the continuous improvement of the economic level, the willingness of Chinese people to participate in sports is showing an upward trend. Objective: It aimed to discuss the simulation of the relationship between joint motion amplitude (JMA) and motion damage (MD) via a rough set decisionmaking algorithm to avoid MD. Based on the rough set decision algorithm, JMA and MD models were constructed, and a motion data decision table was established. Results: The feature strength and the division accuracy of the rough set decision algorithm all showed good accuracy. Conclusion: The proposed rough set decision algorithm can describe the relationship between JMA and MD scientifically and effectively, which provided reference value for sports. In the study of MD, it was found that there is a very close relationship between the joint amplitude and MD.[1,2,3] how to scientifically and effectively arrange the load and exercise intensity in training, as well as how to scientifically and effectively grasp the JMA and MD prediction strategies in track and field training, has become an urgent problem in this field.[6,7,8]. The classification problem of inaccurate and incomplete data can be effectively solved thanks to this mathematical tool that is more in line with human cognition
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
