Control of sports exercises and diagnostics of diseases of the musculoskeletal system using hardware and software complex and machine learning algorithm
Authors:
1.
Moscow Institute of Physics and Technology (State University)
(Department of Computational Physics, associate professor)
Moscow, Russian Federation
Moscow, Russian Federation
2.
Acceleration LLC
(specialist po korporativnomu zdorov'yu, reabilitolog)
Moscow, Russian Federation
Moscow, Russian Federation
3.
Acceleration Digital LLC
Moscow, Russian Federation
Moscow, Russian Federation
4.
Lomonosov Moscow State University
Acceleration Digital LLC
Moscow, Russian Federation
Acceleration Digital LLC
Moscow, Russian Federation
5.
Moscow Institute of Physics and Technology (State University)
(Department of Computational Physics, Head of the Department)
Dolgoprudny, Moscow, Russian Federation
Dolgoprudny, Moscow, Russian Federation
Type:
Article
Pages:
from 8
to 12
Status:
Published
Received:
28.12.2023
Accepted:
22.01.2024
Published:
13.03.2024
Subject area:
1.1.10
1.2.1
1.2.2
3.1.33
5.8.5
5.8.6
355.233.22
796.012
004.93
77.00
20.00
02.00.00
32.00.00
49.06.01
22
58
75
5
COM014000
COM018000
COM062000
COM089000
COM077000
COM051300
HEA007000
YAN024040
BIO016000
1.2.1
1.2.2
3.1.33
5.8.5
5.8.6
355.233.22
796.012
004.93
77.00
20.00
02.00.00
32.00.00
49.06.01
22
58
75
5
COM014000
COM018000
COM062000
COM089000
COM077000
COM051300
HEA007000
YAN024040
BIO016000
Language:
English
Keywords:
musculoskeletal system, pose estimation, yoga, dancing, high-intensity interval training
Abstract (English):
The article presents the experience of developing a hardware and software complex designed to monitor the performance of sports exercises and diagnose the state of the athlete’s musculoskeletal system. The algorithms used are described and their significance for the problem being solved is justified.
The article presents the experience of developing a hardware and software complex designed to monitor the performance of sports exercises and diagnose the state of the athlete’s musculoskeletal system. The algorithms used are described and their significance for the problem being solved is justified.
Keywords:
musculoskeletal system, pose estimation, yoga, dancing, high-intensity interval training
musculoskeletal system, pose estimation, yoga, dancing, high-intensity interval training
1. Liu W., Bao Q., Sun Y., Mei T. Recent advances of monocular 2d and 3d human pose estimation: A deep learning perspective. ACM Computing Surveys, 2022, 55 (4), Article 80, pp. 1-41. DOI: https://doi.org/10.1145/3524497
2. Fan Z., Zhu Y., He Y., Sun Q., Liu H., He J. Deep learning on monocular object pose detection and tracking: A comprehensive overview. ACM Computing Surveys, 2022, 55 (4), Article 81, pp. 1-40. DOI: https://doi.org/10.1145/3524496
