Support Vector Machine Analysis on Ground Reaction Force Characteristics of Patients with Patellofemoral Pain in Different Disease Courses
10.16156/j.1004-7220.2025.02.005
- VernacularTitle:不同病程髌股关节痛患者跑步地面反作用力特征的支持向量机分析
- Author:
Pengcheng SHI
1
;
Hanjun LI
;
Huijuan SHI
Author Information
1. 北京体育大学 运动人体科学学院,国家体育总局体能训练与身体机能恢复实验室,北京 100084;北京体育大学 运动康复科学教育部重点实验室,北京 100084
- Publication Type:Journal Article
- Keywords:
patellofemoral pain;
running;
support vector machine;
feature selection;
biomechanics
- From:
Journal of Medical Biomechanics
2025;40(2):284-290
- CountryChina
- Language:Chinese
-
Abstract:
Objective To investigate the dynamic features of patients with patellofemoral pain(PFP)during running by using support vector machine(SVM)classifier and feature selection method,so as to provide a theoretical support for the prevention and rehabilitation of PFP.Methods An SVM classification model was used to classify healthy individuals(n=13),PFP patients with long-term disease course(n=13),and PFP patients with short-term disease course(n=10)based on their dynamic features during running.The most effective minimum feature set was selected through feature selection method.Results The accuracy rate of the constructed classification model was 83.3%.The minimum feature set selected contained 3 key features.PFP patients with short-term disease course showed a delay in the appearance of impact valleys and active peaks,while PFP patients with long-term disease course showed a lower impact peak-valley slope.Conclusions PFP patients with short-term disease course mainly showed a prolonged shock absorption process and a delayed propulsion action,while PFP patients with long-term disease course showed the most significant feature of having a lower vertical reaction force impact peak-valley slope.These features revealed the specific characteristics of PFP at different stages of the disease,providing a basis for developing individualized rehabilitation programs.
