Gait feature extraction and generation method for ankle joint ligament injury and system

A technology for gait characteristics and ligament injury, which is applied in neural learning methods, biological neural network models, and light-based diagnosis. sexual effect

Active Publication Date: 2020-06-26
UNIV OF SCI & TECH BEIJING
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is to provide a gait feature extraction and generation method and system for ankle ligament injuries, so as to solve the problems of low quality and quantity of feature samples in the existing intelligent diagnosis and decision-making system for ankle ligament injuries. grossly inadequate

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  • Gait feature extraction and generation method for ankle joint ligament injury and system
  • Gait feature extraction and generation method for ankle joint ligament injury and system
  • Gait feature extraction and generation method for ankle joint ligament injury and system

Examples

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no. 1 example

[0072] This embodiment provides a gait feature extraction and generation method for ankle ligament injuries. The gait feature extraction and generation method for ankle ligament injuries includes:

[0073] S101, collecting gait data of the subject;

[0074] It should be noted that, in this embodiment, the above-mentioned S101 is specifically: based on the Heidelberg foot measurement method, establish 17 sub-sections of the lower limbs covering the lower leg, ankle joint, heel, midfoot and toe. A foot and ankle motion measurement model of bony landmark points; based on the foot and ankle motion measurement model, the gait data of the subject is collected by an optical motion capture system; wherein,

[0075] The characteristic points measured on the calf part include: the inner and outer marker points of the knee joint along the direction of the maximum distance of the knee joint bending axis, the most protruding marker point of the tibial tuberosity, and the tibial trisection ...

no. 2 example

[0119] see Figure 1 to Figure 5 , this embodiment provides a gait feature extraction and generation method for ankle ligament injuries, the method is as follows figure 1 shown, including the following steps:

[0120] S101, constructing a foot and ankle motion measurement model based on the Heidelberg foot measurement method;

[0121] It should be noted that, in this embodiment, as shown in FIG. 2 , the feature marker points involved in the model of this embodiment cover the five lower limb parts of the calf, ankle joint, heel, midfoot, and toe:

[0122] ① Measure 5 feature points on the lower leg, including: the inner and outer marker points (MEP, LEP) of the knee joint along the direction of the maximum distance of the knee joint bending axis; the most protruding marker point of the tibial tuberosity (TTU); points (SH1, SH2);

[0123] ② Two feature points were measured on the ankle joint, specifically including: the inner and outer malleolus markers (MML, LML) along the d...

no. 3 example

[0163] see Image 6 , the present embodiment provides a gait feature extraction and generation system for ankle ligament injuries, the gait feature extraction and generation system for ankle ligament injuries includes:

[0164] A foot and ankle motion measurement module, which is used to collect gait data of the subject;

[0165] A data preprocessing module, the data preprocessing module is used to preprocess the collected gait data;

[0166] A gait phase segmentation module, the gait phase segmentation module is used to perform gait cycles on the preprocessed gait data according to the spatial coordinate positions of the feature marker points according to the common characteristics of the gait and the actual movement conditions of the individual subjects and gait phase automatic segmentation;

[0167] A gait feature space construction module, the gait feature space construction module is used to perform hypothesis testing on the characteristics of each dimension of the inju...

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Abstract

The invention provides a gait feature extraction and generation method for ankle joint ligament injury and a system. The gait feature extraction and generation method includes the steps of ankle motion measurement, data preprocessing, gait phase segmentation, gait feature space construction, gait feature generating, authenticity and generative feature correlation evaluation and visual verificationof generative feature validity. The problems of low feature quality and insufficient sample size in an existing medical system are solved. By collecting gait data of a subject and aiming at the anklejoint ligament injury, a small sample data set of an injury group and a control group is established, feature refinement comparison and analysis are carried out based on an anthropometric method, a gait feature space of ankle joint injury is established, gait feature generation and validity verification are carried out, and a large amount of high-quality and efficient feature data support based on anthropometry is provided for research and application in related fields such as intelligent ankle injury diagnosis and decision-making based on big data, precise construction of rehabilitation programs, and development of assisted exoskeleton robots.

Description

technical field [0001] The invention relates to the technical field of intelligent analysis and processing of medical data, in particular to a gait feature extraction and generation method and system for ankle ligament injuries. Background technique [0002] With the rise of outdoor sports, sports medicine has become one of the public health issues of increasing concern around the world. Accelerating the research process of its intelligent and precise diagnosis and treatment has gained the consensus of the medical, industrial and academic circles. At present, only relying on auxiliary examination methods such as medical history collection, physical examination, X-ray film and nuclear magnetic resonance for clinical diagnosis and injury assessment obviously cannot meet the actual diagnosis and treatment needs for accurate characterization of human motor function. Therefore, optical motion capture systems are gradually It is widely used in the fields of clinical medical diagno...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/11A61B5/00G06K9/00G06K9/46G06K9/62G06N3/04G06N3/08
CPCA61B5/112A61B5/1127A61B5/0059G06N3/08G06V40/25G06V20/49G06V10/462G06N3/045G06F18/241
Inventor 刘欣王莉张德政任继平赵辰阿孜古丽.吾拉木谢永红栗辉
Owner UNIV OF SCI & TECH BEIJING
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