Análisis electromiográfico durante la marcha humana en estudiantes universitarios de Chile.

  1. Arriagada Nuñez, Victor 1
  2. Álvarez Zuñiga, Miguel 1
  3. Mansilla Sepúlveda, Juan 2
  4. Véliz Burgos, Alex 3
  5. Parada-Ulloa, Marcos 4
  1. 1 Universidad de Las Américas
  2. 2 Universidad Católica de Temuco
    info

    Universidad Católica de Temuco

    Temuco, Chile

    ROR https://ror.org/051nvp675

  3. 3 Universidad de Los Lagos
    info

    Universidad de Los Lagos

    Osorno, Chile

    ROR https://ror.org/05jk8e518

  4. 4 Universidad Adventista de Chile
    info

    Universidad Adventista de Chile

    Chillán, Chile

    ROR https://ror.org/038j0b276

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Journal:
Journal of sport and health research

ISSN: 1989-6239

Year of publication: 2024

Issue Title: Enero - Abril

Volume: 16

Issue: 1

Type: Article

DOI: 10.58727/JSHR.97206 DIALNET GOOGLE SCHOLAR lock_openOpen access editor

More publications in: Journal of sport and health research

Abstract

Objective: To characterize the muscle activity profile in university students from the city of Santiago de Chile. Material and methods: The profile of muscle activity in certain key muscles in the lower limb was measured, using surface electromyography, in male students of the kinesiology career at the Universidad De Las Américas aged 20 to 24 years. The SENIAM standard was used for the positioning of the electrodes, where the signal was analyzed and processed using MATLAB software, with signal filtering using ICA. Results: The results indicate that the muscle activity profile does not differ from the literature, except for the biceps femoris muscle, which presents two muscle activations during the gait cycle, one between 40 to 60% and another at 90% at 10% of the cycle. Discussion and Conclusion: Further studies with a larger number of participants are suggested to extrapolate the data to the total population in our country. 

Bibliographic References

  • Agostini, V., Nascimbeni, A., Gaffuri, A., Imazio, P., Benedetti, M. G., & Knaflitz, M. (2010). Normative EMG activation patterns of school-age children during gait. Gait & posture, 32(3), 285-289.
  • Andrade, A. O., Kyberd, P., & Nasuto, S. J. (2008). The application of the Hilbert spectrum to the analysis of electromyographic signals. Information Sciences, 178(9), 2176-2193.
  • Barre, A., & Armand, S. (2014). Biomechanical ToolKit: Open-source framework to visualize and process biomechanical data. Computer methods and programs in biomedicine, 114(1), 80-87.
  • Benedetti, M. G., Agostini, V., Knaflitz, M., & Bonato, P. (2012). Muscle activation patterns during level walking and stair ambulation. Applications of EMG in clinical and sports medicine, 8(2), 117-130.
  • Chen, M., & Zhou, P. (2015). A novel framework based on FastICA for high density surface EMG decomposition. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 24(1), 117-127.
  • Muñoz-Cofré, R., Medina-González, P., & Escobar-Cabello, M. (2016). Análisis del comportamiento temporal de variables fisiológicas y de esfuerzo en sujetos instruidos en la prueba de marcha de 6 minutos: complemento a la norma de la Sociedad Americana del Tórax. Fisioterapia, 38(1), 20-27.
  • Neumann, D. A. (2010). Kinesiology of the musculoskeletal system; Foundation for rehabilitation. Mosby & Elsevier.
  • Nuin Amuriza, I. (2015). Electromiografía de superficie (EMGs) en el diagnóstico y detección de la fatiga en ciclistas.
  • Ounpuu, S. (1994). The biomechanics of walking and running. Clinics in sports medicine, 13(4), 843-863.
  • Perry, J., & Burnfield, J. M. (2010). Gait analysis. Normal and pathological function 2nd ed. California: Slack.
  • Piedras-Jorge, C., Meléndez-Moral, J. C., & Tomás-Miguel, J. M. (2010). Beneficios del ejercicio físico en población mayor institucionalizada. Revista española de Geriatría y Gerontología, 45(3), 131-135.
  • Pizzolato, S., Tagliapietra, L., Cognolato, M., Reggiani, M., Müller, H., & Atzori, M. (2017). Comparison of six electromyography acquisition setups on hand movement classification tasks. PloS one, 12(10), e0186132.
  • Silva, L. M., & Stergiou, N. (2020). The basics of gait analysis. Biomechanics Gait Analy, 164, 231.
  • Sousa, A. D., & Tavares, J. M. R. (2010). A marcha humana: uma abordagem biomecânica. In I International Congress of Health Gaia-Porto.
  • Stegeman, D., & Hermens, H. (2007). Standards for surface electromyography: The European project Surface EMG for non-invasive assessment of muscles (SENIAM). Enschede: Roessingh Research and Development, 10, 8-12.
  • Toloza, S. M., & Gómez-Conesa, A. (2007). El Cuestionario Internacional de Actividad Física. Un instrumento adecuado en el seguimiento de la actividad física poblacional. Revista iberoamericana de fisioterapia y kinesiología, 10(1), 48-52.
  • Trinler, U., Schwameder, H., Baker, R., & Alexander, N. (2019). Muscle force estimation in clinical gait analysis using AnyBody and OpenSim. Journal of biomechanics, 86, 55-63.
  • Vázquez, S. C., Gómez, F. P., Vadillo, A. Á., & Rodríguez, L. P. R. (2003). Análisis de la marcha. Factores Moduladores. Biociencias, 1, 20.
  • Veale, J. (2014). Edinburgh handedness inventoryShort Form: A revised versión based on confirmatory factor analysis. Laterality, 19(2), 164-177.
  • Wang, J., Dai, Y., Kang, T., & Si, X. (2021, August). Research on Gait Recognition Based on Lower Limb EMG Signal. In 2021 IEEE International Conference on Mechatronics and Automation (ICMA) (pp. 212-217). IEEE.
  • White, S. C., Yack, H. J., & Winter, D. A. (1989). A three-dimensional musculoskeletal model for gait analysis. Anatomical variability estimates. Journal of biomechanics, 22(8-9), 885-893.
  • White, S. C., & Winter, D. A. (1992). Predicting muscle forces in gait from EMG signals and musculotendon kinematics. Journal of Electromyography and Kinesiology, 2(4), 217-231.
  • Winter, D. A., Fuglevand, A. J., & Archer, S. E. (1994). Crosstalk in surface electromyography: theoretical and practical estimates. Journal of Electromyography and Kinesiology, 4(1), 15-26.
  • Yusuf, S. I., Adeshina, S., & Boukar, M. M. (2019, December). Parameters for Human Gait Analysis: A Review. In 2019 15th International Conference on Electronics, Computer and Computation (ICECCO) (pp. 1-4). IEEE.
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