Athlete athletic injury risk early warning method

A risk early warning and sports injury technology, applied in special data processing applications, instruments, biological neural network models, etc., can solve problems such as many characteristic parameters, long learning and training time, and large neural network scale

Active Publication Date: 2014-12-10
钟亚平 +2
View PDF3 Cites 26 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the use of neural networks for sports injury risk assessment has problems such as too many selected feature parameters, too large a ne

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Athlete athletic injury risk early warning method
  • Athlete athletic injury risk early warning method
  • Athlete athletic injury risk early warning method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0087] The present invention will be further described in detail below in conjunction with the accompanying drawings and preferred embodiments.

[0088] 1. Analysis of factors related to early warning of sports injury risk

[0089] a. Internal injury factor

[0090] (1) age

[0091] Table-1 Injury Risk Assessment of Track and Field Athletes' Age Index Injuries

[0092]

[0093] (2) Gender

[0094] Table-2 Injury risk assessment of gender indicators in track and field jumping sports

[0095]

[0096] (3) Menstrual cycle

[0097] Table-3 Injury risk assessment of menstrual cycle indicators of track and field athletes

[0098]

[0099] (4) Physical training level (sports level)

[0100] Table-4 Injury Risk Assessment of Track and Field Athletes' Sports Level (Physical Training Level)

[0101]

[0102] (5) History of injury

[0103] Table-5 Injury risk assessment of track and field athletes injury history indicators

[0104]

[0105] (6) Injury recovery sta...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses an athlete athletic injury risk early warning method. On the bases of reference to models provided by foreign scholars and comprehensive analysis of track and field athlete athletic injury factors, a track and field athlete motion injury risk early warning injury factor dynamic chain model is provided, based on the model, corresponding factors are selected from an athlete risk early warning database, and a track and field athlete motion injury risk early warning injury factor dynamic chain quantitative model is established through the analytic hierarchy process. Index data are discretized according to an SOM neutral network discretization method, a decision table is simplified according to a method based on a discernibility matrix in a rough set, an RBF neutral network is established based on the simplified decision table, the RBF neutral network is trained, and finally a correct diagnosis result is acquired. By the adoption of the method, accurate early warning can be conducted on athletic injuries, the athlete athletic injury risk grade is effectively predicted, and treatment and prevention of the athletic injuries are facilitated.

Description

technical field [0001] The invention relates to a method for early warning of athlete's sports injury risk based on rough set-neural network. Background technique [0002] In track and field sports, there are many factors related to sports injuries, including internal injury factors (age, gender, injury history, etc.), external injury factors (field, equipment, weather, etc.), inducing stimulus conditions (training volume, competition density, etc.) etc.), how to find out the relationship between them and the risk of sports injury among so many factors is a daunting task. Moreover, among these factors, there are not only indicators that can be accurately measured, such as physiological and biochemical indicators, but also some qualitative indicators, such as past medical history, body shape characteristics, etc., and the indicators measured by each athlete in the past data are not the same. A comprehensive assessment of sports injury risk is a very difficult task. Radial B...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06F19/00G06N3/02
Inventor 钟亚平胡卫红刘鹏
Owner 钟亚平
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap