Gait Analysis And Deep Learning For Overuse Injury Detection In Outstanding Distance Runners
Rev. int. med. cienc. act. fis. deporte
; 24(95): 1-13, mar.-2024. ilus, graf, tab
Article
in English
| IBECS
| ID: ibc-ADZ-317
Responsible library:
ES1.1
Localization: ES15.1 - BNCS
ABSTRACT
Injuries caused by overuse are common in long-distance runners, and early detection of overuse-induced injuries can assist coaches in adjusting training programs to avoid further development of injuries and effectively prevent serious injuries. Gait research is an important tool in distance running research, through the athlete's gait parameters can obtain the athlete's movement status and injury. However, the traditional less research requires rich experience guidance, which is not conducive to widespread promotion. In this paper, deep learning technology is utilized to construct an athlete overuse injury gait detection model. Through the automatic analysis of the athletes less parameters to detect whether there is overuse-induced injury, early detection of injury trends, to avoid injury aggravation. Through experiments, it is verified that the model can effectively identify the gait parameter characteristics of overuse injury in excellent athletes. (AU)
Full text:
Available
Collection:
National databases
/
Spain
Health context:
SDG3 - Target 3.8 Achieve universal access to health
/
SDG3 - Health and Well-Being
Health problem:
Delivery Arrangements
/
Target 3.3: End transmission of communicable diseases
Database:
IBECS
Main subject:
Primary Health Care
/
Ambulatory Surgical Procedures
/
Quality of Life
/
Referral and Consultation
/
Asthma
/
Wounds and Injuries
/
Nutrition Assessment
/
Penile Prosthesis
/
Euthanasia
/
Predictive Value of Tests
Type of study:
Diagnostic study
/
Practice guideline
/
Prognostic study
/
Risk factors
/
Systematic review
Aspects:
Social determinants of health
/
Patient-preference
Limits:
Humans
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Child
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Male
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Adolescent
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Adult
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Female
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Aged
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Animals
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Child, preschool
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Infant
Country/Region as subject:
Europa
Language:
Spanish
/
English
Journal:
Allergol. immunopatol
/
Actas urol. esp
/
Cir. mayor ambul
/
Cuad. bioét
/
Gastroenterol. hepatol. (Ed. impr.)
/
J. investig. allergol. clin. immunol
/
Nutr. hosp
/
Rev. esp. podol
/
Rev. int. med. cienc. act. fis. deporte
Year:
2023
/
2021
/
2022
/
2024
Document type:
Article
Institution/Affiliation country:
Hospital Clínico Universitario de Valladolid/España
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Advanz Pharma Specialty Medicine Spain SLU/España
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Boston Scientific Iberia/España
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CUF Descobertas Hospital/Portugal
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Capital University of Physical Education and Sports/China
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Casa di Cura Villa Montallegro/Italy
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Centro Hospitalar Lisboa Norte/Portugal
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Centro Hospitalar São João/Portugal
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Centro Hospitalar Universitário Algarve/Portugal
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Centro Hospitalar Universitário Coimbra/Portugal