Int J Sports Med 2018; 39(12): 909-915
DOI: 10.1055/a-0644-3784
Training & Testing
© Georg Thieme Verlag KG Stuttgart · New York

Neuromuscular Parameters Predict the Performance in an Incremental Cycling Test

Oscar García-García
1   Faculty of Education and Sport Sciences, University of Vigo, Pontevedra, Spain
,
Alba Cuba-Dorado
1   Faculty of Education and Sport Sciences, University of Vigo, Pontevedra, Spain
,
Diego Fernández-Redondo
2   Cardiology Service, Complex Hospital of Pontevedra, Pontevedra, Spain
,
José López-Chicharro
3   Grupo FEBIO, Universidad Complutense de Madrid, Madrid, Spain
› Author Affiliations
Further Information

Publication History



accepted 06 June 2018

Publication Date:
07 August 2018 (online)

Abstract

The aim was to determine the predictive capacity of neuromuscular parameters on physiological predictors of performance related to pedaling power. The sample comprised fifty elite cyclists. On the same day, they were given a neuromuscular evaluation with tensiomyography (TMG) and then performed an effort test on a cycle ergometer until exhaustion. The TMG recorded the maximum radial muscle belly displacement, contraction time, delay time, derivative normalized response speed, and lateral symmetry. Peak power output (Wpeak·kg−1), effort time, maximum lactate concentration, power in the first lactate threshold, and power in the second lactate threshold were recorded in the effort test. Linear regression analysis was used to determine the explanatory capacity of neuromuscular parameters on potential cycling performance indicators. A higher Wpeak·kg−1 during a maximal incremental test on the cycle ergometer can be predicted moderately (R2=0.683; R2a=0.615; R=0.826; Std. Error=0.26017; p<0.001) by a longer rectus femoris contraction time and a greater radial muscle belly displacement of the vastus lateralis and vastus medialis as well as a slower normalized response speed of the biceps femoris. In conclusion, neuromuscular parameters can partially explain performance in a specific cycling test until exhaustion.

 
  • References

  • 1 Bentley DJ, McNaughton LR, Thompson D, Vleck VE, Batterham AM. Peak power output, the lactate threshold, and time trial performance in cyclists. Med Sci Sports Exerc 2001; 33: 2077-2081
  • 2 Bini RR, Carpes FP, Diefenthaeler F, Mota CB, Guimaraes ACS. Physiological and electromyographic responses during 40-km cycling time trial: Relationship to muscle coordination and performance. J Sci Med Sport 2008; 11: 363-370
  • 3 Carrasco L, Sañudo B, de Hoyo M, Pradas F, Da Silva ME. Effectiveness of low-frequency vibration recovery method on blood lactate removal, muscle contractile properties and on time to exhaustion during cycling at VO2max power output. Eur J Appl Physiol 2011; 111: 2271-2279
  • 4 Castronovo AM, Conforto S, Schmid M, Bibbo D, D’Alessio T. How to assess performance in cycling: The multivariate nature of influencing factors and related indicators. Front Physiol 2013; 4: 116-116
  • 5 Dahmane R, Djordjevič S, Šimunič B, Valenčič V. Spatial fiber type distribution in normal human muscle: Histochemical and tensiomyographical evaluation. J Biomech 2005; 38: 2451-2459
  • 6 Dahmane R, Valenčič V, Knez N, Erzen I. Evaluation of the ability to make non-invasive estimation of muscle contractile properties on the basis of the muscle belly response. Med Biol Eng Comput 2001; 39: 51-55
  • 7 de Paula Simola RÁ, Harms N, Raeder C, Kellmann M, Meyer T, Pfeiffer M, Ferrauti A. Assessment of neuromuscular function after different strength training protocols using tensiomyography. J Strength Cond Res 2015; 29: 1339-1348
  • 8 de Paula Simola RÁ, Raeder C, Wiewelhove T, Kellmann M, Meyer T, Pfeiffer M, Ferrauti A. Muscle mechanical properties of strength and endurance athletes and changes after one week of intensive training. J Electromyogr Kinesiol 2016; 30: 73-80
  • 9 Faria EW, Parker DL, Faria IE. The science of cycling: physiology and training. Sports Med 2005; 35: 285-312
  • 10 García-García O. The relationship between parameters of tensiomyography and potential performance indicators in professional cyclists. Rev Int Med Cienc Ac 2013; 13: 771-781
  • 11 García-García O, Cancela-Carral JM, Martínez-Trigo R, Serrano-Gómez V. Differences in the contractile properties of the knee extensor and flexor muscles in professional road cyclists during the season. J Strength Cond Res 2013; 27: 2760-2767
  • 12 García-Manso JM, Rodríguez-Matoso D, Sarmiento S, de Saa Y, Vaamonde D, Rodríguez-Ruiz D, Da Silva-Grigoletto ME. Effect of high-load and high-volume resistance exercise on the tensiomyographic twitch response of biceps brachii. J Electromyogr Kinesiol 2012; 22: 612-619
  • 13 García-Manso JM, Rodríguez-Ruiz D, Rodríguez-Matoso D, de Saa Y, Sarmiento S, Quiroga M. Assessment of muscle fatigue after an ultra-endurance triathlon using tensiomyography (TMG). J Sports Sci 2011; 29: 619-625
  • 14 Gil S, Loturco I, Tricoli V, Ugrinowitsch C, Kobal R, Cal Abad CC, Roschel H. Tensiomyography parameters and jumping and sprinting performance in Brazilian elite soccer players. Sports Biomech 2015; 14: 340-350
  • 15 Giovanelli N, Giovanelli N, Taboga P, Rejc E, Simunic B, Antonutto G, Lazzer S. Effects of an uphill marathon on running mechanics and lower-limb muscle fatigue. Int J Sports Physiol Perform 2016; 11: 522-529
  • 16 Harriss DJ, Macsween A, Atkinson G. Standards for ethics in sport and exercise science research: 2018 update. Int J Sports Med 2017; 38: 1126-1131
  • 17 Hawley JA, Noakes TD. Peak power output predicts maximal oxygen uptake and performance time in trained cyclists. Eur J Appl Physiol 1992; 65: 79-83
  • 18 Hug F, Dorel S. Electromyographic analysis of pedaling: a review. J Electromyogr Kinesiol 2009; 19: 182-199
  • 19 Hunter AM, Galloway SD, Smith IJ, Tallent J, Ditroilo M, Fairweather MM, Howatson G. Assessment of eccentric exercise-induced muscle damage of the elbow flexors by tensiomyography. J Electromyogr Kinesiol 2012; 22: 334-341
  • 20 Križaj D, Šimunič B, Žagar T. Short-term repeatability of parameters extracted from radial displacement of muscle belly. J Electromyogr Kinesiol 2008; 18: 645-651
  • 21 Loturco I, Gil S, Laurino CFdS, Roschel H, Kobal R, Cal Abad CC, Nakamura FY. Differences in muscle mechanical properties between elite power and endurance athletes: A comparative study. J Strength Cond Res 2015; 29: 1723-1728
  • 22 Loturco I, Pereira LA, Kobal R, Kitamura K, Ramírez-Campillo R, Zanetti V, Cal Abad CC, Nakamura FY. Muscle contraction velocity: A suitable approach to analyze the functional adaptations in elite soccer players. J Sports Sci Med 2016; 15: 483-491
  • 23 Lucía A, Hoyos J, Chicharro JL. Physiology of professional road cycling. Sports Med 2001; 31: 325-337
  • 24 Lucía A, Hoyos J, Pardo J, Chicharro JL. Metabolic and neuromuscular adaptations to endurance training in professional cyclist: A longitudinal study. Jpn J Physiol 2000; 50: 381-388
  • 25 Martín-Rodríguez S, Loturco I, Hunter AM, Rodríguez-Ruiz D, Munguía-Izquierdo D. Reliability and measurement error of tensiomyography to assess mechanical muscle function: A systematic review. J Strength Cond Res 2017; 31: 3524-3536
  • 26 Macgregor LJ, Hunter AM, Orizio C, Fairweather MM, Ditroilo M. Assessment of skeletal muscle contractile properties by radial displacement: The case for tensiomyography. Sports Med. 2018; 48: 1607-1620
  • 27 Pallarés JG, Morán-Navarro R, Ortega JF, Fernández-Elías VE, Mora-Rodriguez R. Validity and reliability of ventilatory and blood lactate thresholds in welltrained cyclists. PLoS One 2016; 11 e0163389
  • 28 Perotto AO, Delagi EF, Lazzeti J, Morrison D. Anatomic Guide for the Electromyographer: The Limbs. Springfield: Charles C. Thomas; 2005: 228-260
  • 29 Pišot R, Narici MV, Šimunič B, De Boer M, Seynnes O, Jurdana M, Biolo G, Mekjavić IB. Whole muscle contractile parameters and thickness loss during 35-day bed rest. Eur J Appl Physiol 2008; 104: 409-414
  • 30 Rodríguez-Ruiz D, Rodríguez-Matoso D, Quiroga ME, Sarmiento S, García-Manso JM, Da Silva-Grigoletto ME. Study of mechanical characteristics of the knee extensor and flexor musculature of volleyball players. Eur J Sport Sci 2012; 12: 399-407
  • 31 Šimunič B. Between-day reliability of a method for non-invasive estimation of muscle composition. J Electromyogr Kinesiol 2012; 22: 527-530
  • 32 Šimunič B, Degens H, Rittweger J, Narici M, Mekjavic I, Pisot R. Noninvasive estimation of myosin heavy chain composition in human skeletal muscle. Med Sci Sports Exerc 2011; 43: 1619-1625
  • 33 Sjödin B, Jacobs I. Onset of blood lactate accumulation and marathon running performance. Int J Sports Med 1981; 23-26
  • 34 Svedahl K, MacIntosh BR. Anaerobic threshold: The concept and methods of measurement. Can J Appl Physiol 2003; 28: 299-323
  • 35 Watsford M, Ditroilo M, Fernández-Peña E, D'Amen G, Lucertini F. Muscle stiffness and rate of torque development during sprint cycling. Med Sci Sports Exerc 2010; 42: 1324-1332
  • 36 Zubac D, Simunic B. Skeletal muscle contraction time and tone decrease after 8 weeks of plyometric training. J Strength Cond Res 2017; 31: 1610-1619