Preview

Doklady BGUIR

Advanced search

Algorithm for the analysis of kinematic characteristics of running

https://doi.org/10.35596/1729-7648-2020-18-8-37-45

Abstract

Biomechanics of motor actions solves the problems of analysis of external motor events - kinematic and dynamic movement parameters. Inertial measurement devices such as gyroscope and accelerometer are used for biomechanical analysis of human movements. The paper describes an algorithm for analysis of kinematic characteristics of the running based on inertial gyro signals. Running is used to estimate the physical performance, endurance, coordination abilities of a person. Gyroscope signals were registered using the TrignoTM Wireless System. For data analysis in the MATLAB, the software for automated evaluation of electromyographic and biomechanical motion patterns was developed. The algorithm allows one to calculate time, spatial and spatial-to-time parameters of motion, symmetry of movements of the left and right limbs, and also stability of repetition of biomechanical movement pattern. The algorithm includes the following stages: 1) adaptive filtering of signals; 2) identification of movement phases; 3) calculation of spatial and time symmetry of left and right limbs; 4) analysis of the repetition stability of biomechanical movement pattern. The proposed algorithm was used to estimate the motor coordination potential of high-skilled athletes in longdistance running. The research made it possible to estimate individual features of work of each group of muscles for each sportsman while performing a test task with stepwisely increasing load on a running track. This approach is a tool to detect asymmetric work of paired muscle groups and of muscle groups with irrational workability. The proposed algorithm for the analysis of running kinematic characteristics can be used to develop new criteria for evaluating the effectiveness of solving a movement problem, as well as to assess the correctness of the movement technique and identify errors that can lead to injuries.

About the Authors

N. S. Davydova
Belarusian State University of Informatics and Radioelectronics
Belarus

Davydova N.S., PhD, Аssociate Professor, Associate Professor of the Infocommunication Technologies Department 

220013, Republic of Belarus Minsk, P. Brovka str., 6



V. Е. Vasiuk
Belarusian National Technical University
Belarus

Vasiuk V.Е., PhD (Pedagogics), Аssociate Professor, Head of the Sports Engineering Department

Minsk



N. A. Paramonova
Belarusian National Technical University
Belarus

Paramonova N.А., PhD (Biology), Аssociate Professor, Аssociate Professor of the Sports Engineering Department

Minsk



М. М. Mezhennaya
Belarusian State University of Informatics and Radioelectronics
Belarus

Mezhennaya М.M., PhD, Аssociate Professor, Аssociate Professor of the Engineering Psychology and Ergonomics Department

Minsk



D. I. Guseinov
Belarusian National Technical University
Belarus

Guseinov D.I., PhD student of the Sports Engineering Department

Minsk



References

1. Popov G.I. [Motion biomechanics]. Moscow: Akademiya; 2011. (In Russ.)

2. McGinnis P.M. Biomechanics of sport and exercise. Human Kinetics; 2013.

3. Watkins J. An introduction to biomechanics of sport and exercise. London: Churchill Livingstone; 2007.

4. Khoshnoud F., de Silva C.W. Recent advances in MEMS sensor technology-mechanical applications. IEEE Instrumentation & Measurement Magazine. 2012;15:14-24.

5. Segers V. et al. Biomechanics of spontaneous overground walk-to-run transition. Journal of Experimental Biology. 2013;16:3047-3054.

6. Mayagoitia R.E., Nene A.V., Veltink P.H. Accelerometer and rate gyroscope measurement of kinematics: an inexpensive alternative to optical motion analysis systems. Journal of biomechanics. 2002;35(4):537-542.

7. Looney M. The Basics of MEMS IMU/Gyroscope Alignment. Analog Dialogue. 2015;49:1-6.

8. Antoniou A. Digital signal processing. New York: McGraw-Hill; 2016.

9. Anshel M.H. Sport psychology: From theory to practice. B. Cummings; 2003.

10. Hu G.S. Introduction to digital signal processing. Beijing: Tsinghua University Press; 2005.

11. Zhilyaev A.A. [Biomechanical diagnostics of optimal performance of cyclic movements]. Theory and practice of physical culture. 2001;10:41-43. (In Russ.)

12. Davydova N.S, Osipov A.N., Kulchitsky V.A., Davydov M.V., Mezhennaya M.M. [Estimation of human movement skill variability based on electrophysiological and biomechanical motion parameters]. Doklady BGUIR = Doklady BGUIR. 2012;1(63):40-46. (In Russ.)

13. Davydova N., Lukashevich D., Bykov D., Vasiuk V., Osipov A., Semeniuk A., Mezhennaya M., Davydov M. Аmplitude-time analysis of biomechanical patterns of human motions. Journal Engineering Science. 2020;3:169-181.


Review

For citations:


Davydova N.S., Vasiuk V.Е., Paramonova N.A., Mezhennaya М.М., Guseinov D.I. Algorithm for the analysis of kinematic characteristics of running. Doklady BGUIR. 2020;18(8):37-45. (In Russ.) https://doi.org/10.35596/1729-7648-2020-18-8-37-45

Views: 2693


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 1729-7648 (Print)
ISSN 2708-0382 (Online)