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Home / Journals / Russian Journal of Information Technology in Sports / Volume 1 Issue 3 / Evaluation of Student's Posture Using Motion Video Analysis, Extraction of Anatomical Point Parameters, and Critical Duration of Postures
Evaluation of Student's Posture Using Motion Video Analysis, Extraction of Anatomical Point Parameters, and Critical Duration of Postures
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EVALUATION OF STUDENT'S POSTURE USING MOTION VIDEO ANALYSIS, EXTRACTION OF ANATOMICAL POINT PARAMETERS, AND CRITICAL DURATION OF POSTURES
Rytova Alena 1
Petrov Mihail 2
Simakov Sergey 3
Dubodelov Artem 4
Dyachenko Dmitry 5
Bravyy Yan 6
Onischenko Dmitri 7
Authors:
1.  Moscow Institute of Physics and Technology (State University) (Department of Computational Physics)
from 01.01.2024 until now
Moscow, Russian Federation
2.  Moscow Institute of Physics and Technology (State University) (Kafedra vychislitel'noy fiziki, associate professor)

Moscow, Russian Federation
3.  Moscow Institute of Physics and Technology (State University) (Department of Computational Physics, Head of the Department)

Dolgoprudny, Moscow, Russian Federation
4.  Lomonosov Moscow State University

Acceleration Digital LLC

Moscow, Russian Federation
5.  Acceleration Digital LLC

Moscow, Russian Federation
6.  Sirius University of Science and Technology (Scientific direction "Interdisciplinary sports research" of the Scientific Center for Genetics and Life Sciences, Senior Researcher)

Federal Territory "Sirius", Krasnodar, Russian Federation
7.  Sirius University of Science and Technology
employee

Type:
Article
DOI:
https://doi.org/10.62105/2949-6349-2024-1-3-37-48
EDN:
https://elibrary.ru/ckibql
Pages:
from 37 to 48
Status:
Published
Received:
05.12.2024
Accepted:
25.12.2024
Published:
28.12.2024
Subject area:
VAC 1.1.10 Биомеханика и биоинженерия
VAC 1.2.2 Математическое моделирование, численные методы и комплексы программ
VAC 3.3.9 Медицинская информатика
VAC 3.1.33 Восстановительная медицина, спортивная медицина, лечебная физкультура, курортология и физиотерапия
VAC 5.8.6 Оздоровительная и адаптивная физическая культура
VAC 2.2.12 Приборы, системы и изделия медицинского назначения
UDK 004 Информационные технологии. Компьютерные технологии. Теория вычислительных машин и систем
UDK 796.012 Кинематика. Спортивные движения. Учение о двигательных (моторных) функциях человеческого тела Психологические, анатомические и физиологические признаки и характеристики обозначать с помощью :159.9..., :611..., :612...
GRNTI 50.53 Автоматизация научных исследований
GRNTI 77.00 ФИЗИЧЕСКАЯ КУЛЬТУРА И СПОРТ
GRNTI 20.00 ИНФОРМАТИКА
OKSO 02.00.00 Компьютерные и информационные науки
OKSO 06.00.00 Биологические науки
OKSO 09.00.00 Информатика и вычислительная техника
OKSO 32.00.00 Науки о здоровье и профилактическая медицина
BBK 22 Физико-математические науки
BBK 28 Биологические науки
BBK 58 Прикладные отрасли медицины
BBK 75 Физическая культура и спорт
TBK 5 ПРИКЛАДНЫЕ НАУКИ. ТЕХНИКА. МЕДИЦИНА
BISAC COM014000 Computer Science
BISAC COM018000 Data Processing
BISAC COM089000 Data Visualization
BISAC COM077000 Mathematical & Statistical Software
BISAC TEC059000 Biomedical
Language:
Russian, English
Keywords:
biomechanics, computer vision, posture monitoring, pose recognition, posture analysis
Abstract and keywords
Abstract (English):
This article discusses the development and implementation of an algorithm for the automatic analysis of schoolchildren's posture using video recordings. The study aims to create an effective tool for detecting posture deviations through biomechanical features, such as shoulder and head tilt angles, distances between anatomical points, and other parameters. The algorithm involves the use of the BlazePose neural network for extracting body key points, identifying irrelevant frames, and analyzing time-series data. The research methodology is based on the application of computer vision techniques and biomechanical feature analysis, followed by data visualization and automated report generation. The results demonstrate that the proposed algorithm effectively identifies posture deviations, providing visual feedback for the prevention and correction of potential disorders. The automation of the process enables large-scale monitoring of schoolchildren's posture and contributes to the prevention of chronic musculoskeletal disorders.

Keywords:
biomechanics, computer vision, posture monitoring, pose recognition, posture analysis
Text
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References

1. Young J., Snell M., Robles O., Kelso J., Kammitsis A., Cloutier N., Cloutier N., DeVries A., Mani, K. Effects of Electronic Usage on the Musculoskeletal System in Adolescents and Young Adults: A Systematic Review. Journal of Musculoskeletal Disorders and Treatment, 2022, 8(2), 114. DOI: https://doi.org/10.23937/2572-3243.1510114 EDN: https://www.elibrary.ru/rnheck

2. Hakala P.T., Saarni L.A., Punam¨aki R.L., Wallenius M.A., Nyg˚ard C.H. Musculoskeletal symptoms and computer use among Finnish adolescents-pain intensity and inconvenience to everyday life: a cross-sectional study. BMC musculoskeletal disorders, 2012, 13, Article number 41. DOI: https://doi.org/10.1186/1471-2474-13-41 EDN: https://www.elibrary.ru/dupqpv

3. Petrov M. N., Kniga A. A., Dyachenko D. L., Dubodelov A. V., Simakov S. S. Control of sports exercises and diagnostics of diseases of the musculoskeletal system using hardware and software complex and machine learning algorithm. Russian Journal of Information Technology in Sports, 2024, 1(1) pp. 8-12. DOI: https://doi.org/10.62105/2949-6349-2024-1-1-9-12 EDN: https://elibrary.ru/qgawoo

4. Mundt M. Born Z., Goldacre M., Alderson J. Estimating ground reaction forces from two-dimensional pose data: a biomechanics-based comparison of alphapose, blazepose, and openpose. Sensors, 2022, 23(1), 78. DOI: https://doi.org/10.3390/s23010078 EDN: https://www.elibrary.ru/szkvnz

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