Journal of Wellbeing Management and Applied Psychology (웰빙융합연구)

Korea Wellbeing Convergence Association (한국웰빙융합학회)
권호 표지
DOI QR코드

DOI QR Code

Extraction of Motor Modules by Autoencoder to Identify Trained Motor Control Ability

  • LEE, Jae-Hyuk (Industry-University Cooperation Foundation, Hanshin University)
  • Received : 2022.04.22
  • Accepted : 2022.06.10
  • Published : 2022.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

Purpose: This pilot study aimed to clarify features of motor module during walking in exercise experts who experienced lately repeated training for sports skill. To identify motor modules, autoencoder machine learning algorithm was used, and modules were extracted from muscle activities of lower extremities. Research design, data and methodology: A total of 10 university students were participated. 5 students did not experience any sports training before, and 5 students did experience sports training more than 5 years. Eight muscle activities of dominant lower extremity were measured. After modules were extracted by autoencoder, the numbers of modules and spatial muscle weight values were compared between two groups. Results: There was no significant difference in the minimal number of motor modules that explain more than 90% of original data between groups. However, in similarity analysis, three motor modules were shown high similarity (r>0.8) while one module was shown low similarity (r<0.5). Conclusions: This study found not only common motor modules between exercise novice and expert during walking, but also found that a specific motor module, which would be associated with high motor control ability to distinguish the level of motor performance in the field of sports.

Keywords

Acknowledgement

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No.2020R1I1A1A0107544511)

References

  1. Barroso, F. O., Torricelli, D., Moreno, J. C., Taylor, J., Gomez-Soriano, J., Bravo-Esteban, E., ... & Pons, J. L. (2014). Shared muscle synergies in human walking and cycling. Journal of neurophysiology, 112(8), 1984-1998. https://doi.org/10.1152/jn.00220.2014
  2. Berniker, M., Jarc, A., Bizzi, E., & Tresch, M. C. (2009). Simplified and effective motor control based on muscle synergies to exploit musculoskeletal dynamics. Proceedings of the National Academy of Sciences, 106(18), 7601-7606. doi: 10.1073/pnas.0901512106
  3. Bernstein, N. (1967). The Coordination and Regulation of Movements Pergamon Press.
  4. Bizzi, E., & Cheung, V. C. (2013). The neural origin of muscle synergies. Frontiers in computational neuroscience, 7, 51. doi: 10.3389/fncom.2013.00051
  5. Chvatal, S. A., & Ting, L. H. (2013). Common muscle synergies for balance and walking. Frontiers in computational neuroscience, 7, 48. doi: 10.3389/fncom.2013.00048
  6. Clark, D. J., Ting, L. H., Zajac, F. E., Neptune, R. R., & Kautz, S. A. (2010). Merging of healthy motor modules predicts reduced locomotor performance and muscle coordination complexity post-stroke. Journal of neurophysiology, 103(2), 844-857. doi: 10.1152/jn.00825.2009
  7. d'Avella, A. (2016). Modularity for motor control and motor learning. Progress in motor control, 3-19.
  8. Diedrichsen, J., Shadmehr, R., & Ivry, R. B. (2010). The coordination of movement: optimal feedback control and beyond. Trends in cognitive sciences, 14(1), 31-39. doi: 10.1016/j.tics.2009.11.004
  9. Esmaeili, S., Karami, H., Baniasad, M., Shojaeefard, M., & Farahmand, F. (2022). The association between motor modules and movement primitives of gait: A muscle and kinematic synergy study. Journal of Biomechanics, 134, 110997. https://doi.org/10.1016/j.jbiomech.2022.110997
  10. Fort-Vanmeerhaeghe, A., Romero-Rodriguez, D., Lloyd, R. S., Kushner, A., & Myer, G. D. (2016). Integrative neuromuscular training in youth athletes. Part II: Strategies to prevent injuries and improve performance. Strength and Conditioning Journal, 38(4), 9-27. doi: 10.1519/SSC.0000000000000234
  11. Hayes, H. B., Chvatal, S. A., French, M. A., Ting, L. H., & Trumbower, R. D. (2014). Neuromuscular constraints on muscle coordination during overground walking in persons with chronic incomplete spinal cord injury. Clinical Neurophysiology, 125(10), 2024-2035. doi: 10.1016/j.clinph.2014.02.001
  12. Hug, F. (2011). Can muscle coordination be precisely studied by surface electromyography?. Journal of electromyography and kinesiology, 21(1), 1-12. doi: 10.1016/j.jelekin.2010.08.009
  13. Israely, S., Leisman, G., & Carmeli, E. (2018). Neuromuscular synergies in motor control in normal and poststroke individuals. Reviews in the Neurosciences, 29(6), 593-612. doi: 10.1515/revneuro-2017-0058
  14. Ivanenko, Y. P., Cappellini, G., Poppele, R. E., & Lacquaniti, F. (2008). Spatiotemporal organization of α-motoneuron activity in the human spinal cord during different gaits and gait transitions. European Journal of Neuroscience, 27(12), 3351-3368. doi: 10.1111/j.1460-9568.2008.06289.x
  15. Ivanenko, Y. P., Poppele, R. E., & Lacquaniti, F. (2004). Five basic muscle activation patterns account for muscle activity during human locomotion. The Journal of physiology, 556(1), 267-282. doi: 10.1113/jphysiol.2003.057174
  16. Kovacs, M. S., Roetert, E. P., & Ellenbecker, T. S. (2008). Efficient deceleration: The forgotten factor in tennis-specific training. Strength & Conditioning Journal, 30(6), 58-69. doi: 10.1519/SSC.0b013e31818e5fbc
  17. Lee JH. (2022) Spatial and Temporal Features of Motor Modules in an individual with Hemiparesis During the Curvilinear Gait: A Pilot Single-Case Study. The Journal of Wellbeing Management and Applied Psychology, 5(1), 1-7
  18. Routson, R. L., Kautz, S. A., & Neptune, R. R. (2014). Modular organization across changing task demands in healthy and poststroke gait. Physiological reports, 2(6), e12055. https://doi.org/10.14814/phy2.12055
  19. Taborri, J., Agostini, V., Artemiadis, P. K., Ghislieri, M., Jacobs, D. A., Roh, J., & Rossi, S. (2018). Feasibility of muscle synergy outcomes in clinics, robotics, and sports: a systematic review. Applied bionics and biomechanics, 2018.