European Journal of Applied Physiology

, Volume 111, Issue 1, pp 101–113 | Cite as

Evaluation of muscle fatigue during 100-m front crawl

  • Igor StirnEmail author
  • Tomaz Jarm
  • Venceslav Kapus
  • Vojko Strojnik
Original Article


The aim of this study was to evaluate muscle fatigue in upper body muscles during 100-m all-out front crawl. Surface electromyogram (EMG) was collected from the pectoralis major, latissimus dorsi and triceps brachii muscles of 11 experienced swimmers. Blood lactate concentration level increased to 14.1 ± 2.9 mmol l−1 5 min after the swim. The velocity, stroke length and stroke rate calculated based on video analysis decreased by 15.0, 5.8 and 7.4%, respectively, during the swim. EMG amplitude of the triceps and the lower part of the latissimus muscles increased, whilst the mean power frequency (MNF) of all muscles significantly decreased by 20–25%. No significant differences in the relative MNF decrease were observed amongst the muscles; however, the differences in the rate of the MNF decrease between the lower part of the latissimus and the triceps brachii muscles were found (P < 0.05). The time of rest between the muscle activation of the two consecutive arm strokes at the end of swimming was extended (P < 0.05). It was concluded that 100-m all-out crawl induced significant fatigue with no evident differences amongst the analysed muscles.


Swimming Stroke parameters EMG Power spectrum Mean frequency 



The authors wish to acknowledge Tine Vizintin of the Faculty of Electrical Engineering of University of Ljubljana for his assistance in EMG signal processing. The study was supported by grants from the Slovenian Research Agency (projects no. LP-6570 and L5-7112) and Slovenian Sport Foundation.


  1. Alberty M, Sidney M, Huot-Marchand F, Hespel JM, Pelayo P (2005) Intracyclic velocity variations and arm coordination during exhaustive exercise in front crawl stroke. Int J Sports Med 26(6):471–475CrossRefPubMedGoogle Scholar
  2. Alberty M, Potdevin F, Dekerle J, Pelayo P, Gorce P, Sidney M (2008) Changes in swimming technique during time to exhaustion at freely chosen and controlled stroke rates. J Sports Sci 26(11):1191–1900CrossRefPubMedGoogle Scholar
  3. Allen DG, Lamb GD, Westerblad H (2008) Skeletal muscle fatigue: cellular mechanisms. Physiol Rev 88(1):287–332CrossRefPubMedGoogle Scholar
  4. Aspenes S, Kjendlie PL, Hoff J, Helgerud J (2009) Combined strength and endurance training in competitive swimmers. J Sports Sci Med 8(3):357–365Google Scholar
  5. Aujouannet YA, Bonifazi M, Hintzy F, Vuillerme N, Rouard AH (2006) Effects of a high-intensity swim test on kinematic parameters in high-level athletes. App Physiol Nutr Metabol 31:150–158CrossRefGoogle Scholar
  6. Behnke RS (2001) Kinetic anatomy. Human Kinetics Publishers, United StatesGoogle Scholar
  7. Bigland-Ritchie B (1981) EMG and fatigue of human voluntary and stimulated contractions. In: Porter R, Whelen J (eds) Human muscle fatigue: physiological mechanisms. CIBA foundation symposium 82. Pitman Medical, LondonGoogle Scholar
  8. Bigland-Ritchie B, Woods JJ (1984) Changes in muscle contractile properties and neural control during human muscular fatigue. Muscle Nerve 7:691–699CrossRefPubMedGoogle Scholar
  9. Billat V, Faina M, Sardella F, Marini C, Fanton F, Lupo S, Faccini P, de Angelis M, Koralsztein JP, Dalmonte A (1996) A comparison of time to exhaustion at VO2 max in élite cyclists, kayak paddlers, swimmers and runners. Ergonomics 39(2):267–277CrossRefPubMedGoogle Scholar
  10. Bonato P, Gagliati G, Knaflitz M (1996) Analysis of surface myoelectric signals recorded during dynamic contractions. IEEE Eng Med Biol Mag 15(10):102–111CrossRefGoogle Scholar
  11. Bonato P, Roy SH, Knaflitz M, De Luca CJ (2001) Time–frequency parameters of the surface myoelectric signal for assessing muscle fatigue during cyclic dynamic contractions. IEEE transactions on bio-medical engineering 48(7):745–753CrossRefPubMedGoogle Scholar
  12. Bonifazi M, Martelli G, Marugo L, Sardela F, Carli G (1993) Blood lactate accumulation in top level swimmers following competition. J Sports Med Phys Fitness 33:13–18PubMedGoogle Scholar
  13. Brody L, Pollock M, Roy S, De Luca C, Celli B (1991) pH induced effects on median frequency and conduction velocity of the myoelectric signal. J Appl Physiol 71:1878–1885PubMedGoogle Scholar
  14. Caty VY, Rouard AH, Hintzy F, Aujouannet YA, Molinari F, Knaflitz M (2006) Time–frequency parameters of wrist muscles EMG after an exhaustive freestyle test. Revista Portuguesa de Ciencias do Desporto 6:28–30Google Scholar
  15. Christensen H, Sogaard K, Jensen BR, Finsen L, Sjogaard G (1995) Intramuscular and surface EMG power spectrum from dynamic and static contractions. J Electromyogr Kinesiol 5(1):27–36CrossRefPubMedGoogle Scholar
  16. Clarys JP, Massez C, Van der Broeck M, Piette G, Robeaux R (1983) Total telemetric surface EMG of the front crawl. In: Matsui H, Kobayashi K (eds) Biomechanics VIII-B. International series on biomechanics, 4B. Human Kinetics Publishers, ChampaignGoogle Scholar
  17. De Luca CJ (1979) Physiology and mathematics of myoelectric signals. IEEE Trans Biomed Eng 26:313–325CrossRefPubMedGoogle Scholar
  18. De Luca CJ (1984) Myoelectrical manifestation of localized muscular fatigue. Crit Rev Biomed Eng 11:251–279PubMedGoogle Scholar
  19. Dekerle J, Nesi X, Lefevre T, Depretz S, Sidney M, Marchand FH, Pelayo P (2005) Stroking parameters in front crawl swimming and maximal lactate steady state velocity. Int J Sports Med 26(1):53–58CrossRefPubMedGoogle Scholar
  20. Deschodt VJ, Arsac LM, Rouard AH (1999) Relative contribution of arms and legs in humans to propulsion in 25-m sprint front-crawl swimming. Eur J Appl Physiol 80:192–199CrossRefGoogle Scholar
  21. Dimitrova NA, Dimitrov GV (2003) Interpretation of EMG changes with fatigue: facts, pitfalls, and fallacies. J Electromyogr Kinesiol 13:13–36CrossRefPubMedGoogle Scholar
  22. Farina D, Merletti R (2000) Comparison of algorithms for estimation of EMG variables during voluntary isometric contractions. J Electromyogr Kinesiol 10:337–350CrossRefPubMedGoogle Scholar
  23. Farina D, Fosci M, Merletti R (2002) Motor unit recruitment strategies investigated by surface EMG variables. J Appl Physiol 92:235–247CrossRefPubMedGoogle Scholar
  24. Fernandes RJ, Billat VL, Cruz AC, Colaço PJ, Cardoso CS, Vilas-Boas JP (2006) Does net energy cost of swimming affect time to exhaustion at the individual’s maximal oxygen consumption velocity? J Sports Med Phys Fitness 46(3):373–380PubMedGoogle Scholar
  25. Fitts RH (1994) Cellular mechanisms of muscle fatigue. Physiol Rev 74:49–89PubMedGoogle Scholar
  26. Gabriel DA, Kamen G (2009) Experimental and modeling investigation of spectral compression of biceps brachii SEMG activity with increasing force levels. J Electromyogr Kinesiol 19:437–448CrossRefPubMedGoogle Scholar
  27. Gazzoni M, Farina D, Merletti R (2004) A new method for the extraction and classification of single motor unit action potentials from surface EMG signals. J Neurosci Methods 136(2):165–177CrossRefPubMedGoogle Scholar
  28. Gerdle B, Eriksson NE, Hagberg C (1988) Changes in the surface electromyogram during increasing isometric shoulder forward flexions. Eur J Appl Physiol Occup Ther 57:404–408CrossRefGoogle Scholar
  29. Gerdle B, Karlsson S, Crenshaw AG, Elert J, Friden J (2000) The influences of muscle fibre proportions and areas upon EMG during maximal dynamic knee extensions. Eur J Appl Physiol 81:2–10CrossRefPubMedGoogle Scholar
  30. Girold S, Calmels P, Maurin D, Milhau N, Chatard JC (2006) Assisted and resisted sprint training in swimming. J Strength Condit Res 20(3):547–554Google Scholar
  31. Havriluk R (2004) Hand force and swimming velocity. In: XVth Federation Internationale de Natation World Congress. IndianapolisGoogle Scholar
  32. Hermens HJ, van Bruggen TAM, Baten CTM, Rutten WLC, Boom HBK (1992) The median frequency of the surface EMG power spectrum in relation to motor unit firing and action potential properties. J Electromyogr Kinesiol 2:15–25CrossRefPubMedGoogle Scholar
  33. Herrmens HJ, Freriks B (1999) European recommendations for surface electromyography, results of the SENIAM project (CD-rom). Roessingh Research and Development, EnschedeGoogle Scholar
  34. Hollander AP, De Groot G, Van Ingen Schenau GJ (1988) Contribution of the legs in front crawl swimming. In: Ungerecht BE, Wilke K, Reischie K (eds) Swimming science V. Human kinetics, Champain, Illinois, pp 39–43Google Scholar
  35. Kapus J, Usaj A, Kapus V, Strumbelj B (2005) The influence of training with reduced breathing frequency with font crawl swimming during a maximal 200 metres front crawl performance. KinSI 11:14–18Google Scholar
  36. Karlsson S, Yu J, Akay M (2000) Time frequency analysis of myoelectric signals during dynamic contractions: a comparative study. IEEE Trans Biomed Eng 47:228–238CrossRefPubMedGoogle Scholar
  37. Keskinen KL, Komi PV (1993) Stroking characteristics of front crawl swimming during exercise. J Appl Biomech 9:219–226Google Scholar
  38. Knaflitz M, Bonato P (1999) Time–frequency methods applied to muscle fatigue assessment during dynamic contractions. J Electromyogr Kinesiol 9:337–350CrossRefPubMedGoogle Scholar
  39. Komi PV, Tesch P (1979) EMG frequency spectrum muscle structure and fatigue during dynamic contractions in man. Eur J Appl Physiol 42:41–50CrossRefGoogle Scholar
  40. Larsson B, Karlsson S, Eriksson M, Gerdle B (2003) Test–retest reliability of EMG and peak torque during repetitive maximum concentric knee extensions. J Electromyogr Kinesiol 13(3):281–287CrossRefPubMedGoogle Scholar
  41. Lindstrom J, Magnusson RT (1977) Interpretation of myoelectric power spectra: a model and its applications. Proc IEEE 65:653–662CrossRefGoogle Scholar
  42. Linssen WH, Jacobs M, Stegeman DF, Joosten EM, Moleman J (1990) Muscle fatigue in McArdle’s disease. Muscle fibre conduction velocity and surface EMG frequency spectrum during ischaemic exercise. Brain 113:1779–1793CrossRefPubMedGoogle Scholar
  43. Lowery M, Nolan P, O’Malley M (2002) Electromyogram median frequency, spectral compression and muscle fiber conduction velocity during sustained sub-maximal contraction of the brachioradialis muscle. J Electromyogr Kinesiol 12:111–118CrossRefPubMedGoogle Scholar
  44. Mac Isaac D, Parker PA, Scott RN (2001) The short time Fourier transform and muscle fatigue assessment in dynamic contraction. J Electromyogr Kinesiol 11:439–449CrossRefGoogle Scholar
  45. Maglischo EW (2003) Swimming fastest. Human kinetics, Champain, ILGoogle Scholar
  46. Masuda T, Miyano H, Sadoyama T (1983) The propagation of motor unit action potential and the location of neuromuscular junction investigated by surface electrode arrays. Electroencephalogr Clin Neurophysiol 55:594–600CrossRefPubMedGoogle Scholar
  47. Masuda K, Masuda T, Sadoyama T, Inaki M, Katsuta S (1999) Changes in surface EMG parameters during static and dynamic fatiguing contractions. J Electromyogr Kinesiol 9:39–46CrossRefPubMedGoogle Scholar
  48. Merletti R, Lo Conte LR (1997) Surface EMG signal processing during isometric contractions. J Electromyogr Kinesiol 7(4):241–250CrossRefPubMedGoogle Scholar
  49. Merletti R, Roy S (1996) Myoelectric and mechanical manifestations of muscle fatigue in voluntary contractions. J Orthop Sports Phys Ther 24:342–353PubMedGoogle Scholar
  50. Merletti R, Knaflitz M, De Luca CJ (1990) Myoelectric manifestations of fatigue in voluntary and electrically elicited contractions. J Appl Physiol 69(5):1810–1820PubMedGoogle Scholar
  51. Merletti R, Lo Conte R, Orizio C (1991) Indices of muscle fatigue. J Electromyogr Kinesiol 1:20–33CrossRefPubMedGoogle Scholar
  52. Merletti R, Rainoldi A, Farina D (2004) Myoelectric manifestations of muscle fatigue. In: Merletti R, Parker FA (eds) Electromyography. IEEE Press, New JerseyCrossRefGoogle Scholar
  53. Miyashita M (1975) Arm action in the crawl stroke. In: Lewillie L, Clarys JP (eds) Swimming II University Park Press, Baltimore, pp 167–173Google Scholar
  54. Nuber GW, Jobe FW, Perry J, Moynes DR, Antonelli D (1986) Fine wire electromyography analysis of muscles of the shoulder during swimming. Am J Sports Med 14:7–11CrossRefPubMedGoogle Scholar
  55. Piette G, Clarys JP (1979) Telemetric EMG of the front crawl movement. In: Terauds J, Bedingfield EW (eds) Swimming III. University Park Press, Baltimore, pp 153–159Google Scholar
  56. Proakis JG, Manolakis DG (1996) Power spectrum estimation. In: Digital signal processing; principles, algorithms, and applications, 3rd edn. Prentice Hall, New JerseyGoogle Scholar
  57. Rouard AH, Clarys JP (1995) Cocontraction in the elbow and shoulder muscles during rapid cyclic movements in an aquatic environment. J Electromyogr Kinesiol 5(3):177–183CrossRefPubMedGoogle Scholar
  58. Rouard AH, Schleihauf RE, Troup JP (1996) Hand forces and phases in freestyle stroke. In: Troup JP, Hollander AP, Strasse D, Trappe SW, Cappaert JM, Trappe TA (eds) Biomechanics and Medicine in swimming VII. Chapman & Hall, London, pp 34–42Google Scholar
  59. Rouard AH, Billat RP, Deschodt V, Clarys JP (1997) Muscular activations during repetitions of sculling movements up to exhaustion in swimming. Arch Physiol Biochem 105:655–662CrossRefPubMedGoogle Scholar
  60. Schleihauf RE (1979) A hydrodynamic analysis of swimming propulsion. In: Teraud J, Bedingfield EW (eds) Swimming III. International series of sport sciences. University Park Press, BaltimoreGoogle Scholar
  61. Scovazzo ML, Browne A, Pink M (1991) The painful shoulder during freestyle swimming: an electromyographic and cinematographic analysis of twelve muscles. Am J Sports Med 19(6):577–582CrossRefPubMedGoogle Scholar
  62. Seifert L, Chollet D (2008) Modelling spatial–temporal and coordinative parameters in swimming. J Sci Med Sport (Epub ahead of print)Google Scholar
  63. Seifert L, Chollet D, Bardy BG (2004) Effect of swimming velocity on arm coordination in the front crawl: a dynamic analysis. J Sports Sci 22(7):651–660CrossRefPubMedGoogle Scholar
  64. Seifert L, Boulesteix L, Carter M, Chollet D (2005) The spatial–temporal and coordinative structures in elite male 100-m front crawl swimmers. Int J Sports Med 26(4):286–293CrossRefPubMedGoogle Scholar
  65. Seifert L, Chollet D, Chatard JC (2007) Kinematic changes during a 100-m front crawl: effects of performance level and gender. Med Sci Sports Exerc 39(10):1784–1793CrossRefPubMedGoogle Scholar
  66. Tella V, Toca-Herrera JL, Gallach JE, Benavent J, González LM, Arellano R (2008) Effect of fatigue on the intra-cycle acceleration in front crawl swimming: a time–frequency analysis. J Biomech 41(1):86–92CrossRefPubMedGoogle Scholar
  67. Toussaint HM, Carol A, Kranenborg H, Truijens MJ (2006) Effect of fatigue on stroking characteristics in an arms-only 100-m front-crawl race. Med Sci Sports Exerc 38:1635–1642CrossRefPubMedGoogle Scholar
  68. Van der Vaart A, Savelberg H, Groot G, Hollander A, Toussaint H, Ingen Schenau G (1987) An estimation of drag in front crawl swimming. J Biomech 20:543–546CrossRefPubMedGoogle Scholar
  69. Viitasalo JH, Komi PV (1977) Signal characteristics of EMG during fatigue. Eur J Appl Physiol Occup Physiol 16:111–121CrossRefGoogle Scholar
  70. Vorontsov AR, Binevsky DA (2003) Swimming velocity, stroke rate and stroke length during maximal 100 m freestyle swim in boy-swimmers 11–16 years of age. In: Chatard JC (ed) Biomechanics and medicine in swimming IX. Saint-Etienne, Universite de Saint-Etienne, pp 195–200Google Scholar
  71. Wakayoshi K, Moritani T, Mutoh Y, Miyashita M (1994) Electromyographic evidence of selective muscle fatigue during competitive swimming. In: Miyashita M, Mutoh Y, Richardson AB (eds) Medicine and Sport Science 39, pp 16–23Google Scholar
  72. Weiss M, Reischle K, Bouws N, Simon G, Weicker H (1988) Relationships of blood lactate to stroke rate and distance per stroke in top female swimmers. In: Ungerechts BE, Wilke K, Reischle K (eds) Swimming science V. Human Kinetics Publishers, Champaign, Illinois, 18:295–303Google Scholar

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Igor Stirn
    • 1
    Email author
  • Tomaz Jarm
    • 2
  • Venceslav Kapus
    • 1
  • Vojko Strojnik
    • 1
  1. 1.Faculty of SportUniversity of LjubljanaLjubljanaSlovenia
  2. 2.Faculty of Electrical EngineeringUniversity of LjubljanaLjubljanaSlovenia

Personalised recommendations