Skip to main content

Advertisement

SpringerLink
Log in

A wearable system for biosignal monitoring in weightlifting

  • Technical Note
  • Published:
Sports Engineering Aims and scope Submit manuscript

Abstract

The use of technological aids in sports has increased in the last years. These tools allow to register the athletes’ movements to evaluate and track their performance over time. With that information, it is possible to design more effective training routines, prevent and treat injuries, and improve performance. This paper describes the design and construction of an electronic system to register joint angle and electromyography signals during the execution of weightlifting exercises. The system was designed to be unobtrusive, energy efficient, and low cost. It was evaluated during the execution of flexion/extension exercises of the arm with weights, and was effective to acquire the signals and transmit them wirelessly in real-time. Electromiography signals were visualized and analyzed with an adequate dynamic range, and angle measurements were performed with error percentages less than 0.8 %.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

References

  1. Adelsberger R, Tröster G (2014) Effects of stretching and warm-up routines on stability and balance during weight-lifting: a pilot investigation. BMC Res Notes 7(1):938

    Article  Google Scholar 

  2. De la Haye Chamorro GL, Mercado Aguirre IM, Contreras-Ortiz SH (2014) Design of an electrogoniometer based on accelerometers for the evaluation of sports gesture in weight lifting. In: Engineering Mechatronics and Automation (CIIMA), 2014 III International Congress of. IEEE, cartagena, pp 1–3

  3. Mercado-Medina EL, Chavarro-Hernandez ZD, Dominguez-Jimenez JA, Contreras-Ortiz SH (2014) Design of an electronic system for monitoring muscle activity in weight lifting. In: Engineering Mechatronics and Automation (CIIMA), 2014 III International Congress of. IEEE, cartagena, pp 1–4

  4. Boseley, S.: London 2012 olympics: how athletes use technology to win medals. Guardian (2012)

  5. Campillo P, Hertogh C, Micallef JP (1999) Puntos críticos del tirón de arrancada en halterofilia. apunts Educación Física y Deportes 55:28–34

  6. Campos J, Poletaev P, Cuesta A, Abella CP, Tébar J (2004) Estudio del movimiento de arrancada en halterofilia durante ciclos de repeticiones de alta intensidad mediante análisis cinemáticos. Motricidad: revista de ciencias de la actividad física y del deporte (12):39–45

  7. Chatzitofis A, Vretos N, Zarpalas D, Daras P (2013) Three-dimensional monitoring of weightlifting for computer assisted training. In: Proceedings of the virtual reality international conference: laval virtual. ACM, p 3

  8. Chen M, Gonzalez S, Vasilakos A, Cao H, Leung VC (2011) Body area networks: a survey. Mob Netw Appl 16(2):171–193

    Article  Google Scholar 

  9. Chen SK, Wu MT, Huang CH, Wu JH, Guo LY, Wu WL (2013) The analysis of upper limb movement and emg activation during the snatch under various loading conditions. J Mech Med Biol 13(01):1350,010

  10. Cheng P, Oelmann B (2010) Joint-angle measurement using accelerometers and gyroscopes. A survey. Instrum Meas IEEE Trans 59(2):404–414

  11. Christ FL, Owen KG, Hudson JL (1996) An exploration of balance and skill in olympic weightlifting. In: International symposium on biomechanics in sport

  12. Comfort P, Allen M, Graham-Smith P (2011) Comparisons of peak ground reaction force and rate of force development during variations of the power clean. J Strength Cond Res 25(5):1235–1239

    Article  Google Scholar 

  13. Dejnabadi H, Jolles BM, Aminian K (2005) A new approach to accurate measurement of uniaxial joint angles based on a combination of accelerometers and gyroscopes. Biomed Eng IEEE Trans 52(8):1478–1484

    Article  Google Scholar 

  14. Diaz Parada R, Martinez Santos J (2014) Study of the lower limp’s angle during weightlifting exercises using an accelerometer-based system. In: Engineering mechatronics and automation (CIIMA), 2014 III International Congress of, pp 1–4

  15. Dong W, Chen I, Lim K, Goh Y et al (2007) Measuring uniaxial joint angles with a minimal accelerometer configuration. In: Proceedings of the 1st international convention on Rehabilitation engineering & assistive technology: in conjunction with 1st Tan Tock Seng Hospital Neurorehabilitation Meeting. ACM, pp 88–91

  16. Faludi R (2010) Building wireless sensor networks: with ZigBee. Arduino, and Processing. O’Reilly Media, XBee

  17. Fong DTP, Chan YY (2010) The use of wearable inertial motion sensors in human lower limb biomechanics studies: a systematic review. Sensors 10(12):11556–11565

    Article  Google Scholar 

  18. Freivalds A (2004) Biomechanics of the upper limbs: mechanics, modelling and musculoskeletal injuries. Taylor & Francis

  19. Garhammer J (1985) Biomechanical profiles of olympic weightlifters. Int J Sport Biomech 1(2):122–130

    Article  Google Scholar 

  20. Gourgoulis V, Aggeloussis N, Antoniou P, Christoforidis C, Mavromatis G, Garas A (2002) Comparative 3-dimensional kinematic analysis of the snatch technique in elite male and female greek weightlifters. J Strength Condition Res 16(3):359–366

    Google Scholar 

  21. Harbili E (2012) A gender-based kinematic and kinetic analysis of the snatch lift in elite weightlifters in 69-kg category. J Sports Sci Med 11(1):162–169

    Google Scholar 

  22. Isaka T, Okada J, Funato K (1996) Kinematic analysis of the barbell during the snatch movement of elite asian weight lifters. JAB 12(4):508–516

    Article  Google Scholar 

  23. Kutz M (2003) Standard handbook of biomedical engineering and design. McGraw-Hill Handbooks Series, McGraw-Hill

  24. Lee JS, Su YW, Shen CC (2007) A comparative study of wireless protocols: Bluetooth, uwb, zigbee, and wi-fi. In: Industrial electronics society, 2007. IECON 2007. 33rd Annual Conference of the IEEE. IEEE, pp 46–51

  25. Liu Y, Chen W (2001)Foot pressure study during pulling phase of snatch lifting. In: ISBS-Conference Proceedings Archive, vol 1

  26. Lloyd DG, Besier TF (2003) An emg-driven musculoskeletal model to estimate muscle forces and knee joint moments in vivo. J Biomech 36(6):765–776

    Article  Google Scholar 

  27. Luca CJD, Gilmore LD, Kuznetsov M, Roy SH (2010) Filtering the surface emg signal: movement artifact and baseline noise contamination. J Biomech 43(8):1573–1579

    Article  Google Scholar 

  28. Mertz L (2013) Technology comes to the playing field: new world of sports promises fewer injuries, better performance. IEEE Pulse 4(5):12–17

    Article  Google Scholar 

  29. Pearson SJ, Young A, Macaluso A, Devito G, Nimmo MA, Cobbold M, Harridge SD (2002) Muscle function in elite master weightlifters. Med Sci Sports Exerc 34(7):1199–1206

    Article  Google Scholar 

  30. Shiffman D (2009) Learning processing: a beginner’s guide to programming images, animation, and interaction. Morgan Kaufmann

  31. Velloso E, Bulling A, Gellersen H (2011) Towards qualitative assessment of weight lifting exercises using body-worn sensors. In: Proceedings of the 13th international conference on Ubiquitous computing. ACM, pp 587–588

  32. Waltz E (2015) The quantified olympian. Spectr IEEE 52(6):44–45

    Article  Google Scholar 

  33. Webster J (1997) Medical instrumentation: application and design, 3rd edn. Wiley

  34. Wei G, Tian F, Tang G, Wang C (2012) A wavelet-based method to predict muscle forces from surface electromyography signals in weightlifting. J Bionic Eng 9(1):48–58

    Article  Google Scholar 

  35. Willemsen ATM, Frigo C, Boom HB (1991) Lower extremity angle measurement with accelerometers-error and sensitivity analysis. Biomed Eng IEEE Trans 38(12):1186–1193

    Article  Google Scholar 

  36. Williamson R, Andrews B (2001) Detecting absolute human knee angle and angular velocity using accelerometers and rate gyroscopes. Med Biol Eng Comput 39(3):294–302

    Article  Google Scholar 

Download references

Acknowledgments

The authors thank the Colombian Science, Technology and Innovation Administrative Department-Colciencias for supporting this project through the “Semilleros de Investigación 2013” Grant.

Author information

Authors and Affiliations

  1. Department of Electrical and Electronic Engineering, Universidad Tecnológica de Bolívar, Parque Industrial y Tecnológico Carlos Vélez Pombo, Km 1 Vía Turbaco, Cartagena de Indias, Colombia

    Isabela M. Mercado-Aguirre, Edgardo L. Mercado-Medina, Zulay D. Chavarro-Hernandez, Juan A. Dominguez-Jimenez & Sonia H. Contreras-Ortiz

Authors
  1. Isabela M. Mercado-Aguirre
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Edgardo L. Mercado-Medina
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zulay D. Chavarro-Hernandez
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Juan A. Dominguez-Jimenez
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Sonia H. Contreras-Ortiz
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sonia H. Contreras-Ortiz.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mercado-Aguirre, I.M., Mercado-Medina, E.L., Chavarro-Hernandez, Z.D. et al. A wearable system for biosignal monitoring in weightlifting. Sports Eng 20, 73–80 (2017). https://doi.org/10.1007/s12283-016-0212-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12283-016-0212-z

Keywords

Search

Navigation