The Physiological, Neuromuscular, and Perceptual Response to Even- and Variable-Paced 10-km Cycling Time Trials

Click name to view affiliation

Tim Veneman
Search for other papers by Tim Veneman in
Current site
Google Scholar
PubMed
Close
,
Wouter Schallig
Search for other papers by Wouter Schallig in
Current site
Google Scholar
PubMed
Close
,
Maaike Eken
Search for other papers by Maaike Eken in
Current site
Google Scholar
PubMed
Close
,
Carl Foster
Search for other papers by Carl Foster in
Current site
Google Scholar
PubMed
Close
, and
Jos J. de Koning
Search for other papers by Jos J. de Koning in
Current site
Google Scholar
PubMed
Close
Restricted access

Background: During self-paced (SP) time trials (TTs), cyclists show unconscious nonrandom variations in power output of up to 10% above and below average. It is unknown what the effects of variations in power output of this magnitude are on physiological, neuromuscular, and perceptual variables. Purpose: To describe physiological, neuromuscular, and perceptual responses of 10-km TTs with an imposed even-paced (EP) and variable-paced (VP) workload. Methods: Healthy male, trained, task-habituated cyclists (N = 9) completed three 10-km TTs. First, an SP TT was completed, the mean workload from which was used as the mean workload of the EP and VP TTs. The EP was performed with an imposed even workload, while VP was performed with imposed variations in workload of ±10% of the mean. In EP and VP, cardiorespiratory, neuromuscular, and perceptual variables were measured. Results: Mean rating of perceived exertion was significantly lower in VP (6.13 [1.16]) compared with EP (6.75 [1.24]), P = .014. No mean differences were found for cardiorespiratory and almost all neuromuscular variables. However, differences were found at individual kilometers corresponding to power-output differences between pacing strategies. Conclusion: Variations in power output during TTs of ±10%, simulating natural variations in power output that are present during SP TTs, evoke minor changes in cardiorespiratory and neuromuscular responses and mostly affect the perceptual response. Rating of perceived exertion is lower when simulating natural variations in power output, compared with EP cycling. The imposed variations in workload seem to provide a psychological rather than a physiological or neuromuscular advantage.

Veneman, Schallig, Foster, and de Koning are with the Dept of Human Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Schallig is also with the Dept of Rehabilitation Medicine at the university. Veneman is also with Dept of Rehabilitation Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands. Eken is with the Div of Orthopedic Surgery, Faculty of Medicine and Health Sciences, Inst of Sport and Exercise Medicine, Stellenbosch University, Tygerberg, South Africa. Foster and de Koning are also with the Dept of Exercise and Sport Science, University of Wisconsin-La Crosse, La Crosse, WI, USA.

Veneman (t.veneman@amsterdamumc.nl) is corresponding author.
  • Collapse
  • Expand
  • 1.

    Foster C, Snyder A, Thompson NN, Green MA, Foley M, Schrager M. Effect of pacing strategy on cycle time trial performance. Med Sci Sports Exerc. 1993;25(3):383388. PubMed ID: 8455455 doi:10.1249/00005768-199303000-00014

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2.

    Foster C, de Koning JJ, Hettinga F, et al. Effect of competitive distance on energy expenditure during simulated competition. Int J Sports Med. 2004;25(3):198204. PubMed ID: 15088244 doi:10.1055/s-2003-45260

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3.

    Abbiss CR, Laursen PB. Describing and understanding pacing strategies during athletic competition. Sports Med. 2008;38(3):239252. PubMed ID: 18278984 doi:10.2165/00007256-200838030-00004

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4.

    Gordon S. Optimising distribution of power during a cycling time trial. Sports Eng. 2005;8(2):8190. doi:10.1007/BF02844006

  • 5.

    Tucker R, Bester A, Lambert E, Noakes TD, Vaughan CL, Gibson ASC. Non-random fluctuations in power output during self-paced exercise. Br J Sports Med. 2006;40(11):912917. PubMed ID: 16980537 doi:10.1136/bjsm.2006.026435

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 6.

    Tucker R. The anticipatory regulation of performance: the physiological basis for pacing strategies and the development of a perception-based model for exercise performance. Br J Sports Med. 2009;43(6):392400. PubMed ID: 19224911 doi:10.1136/bjsm.2008.050799

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7.

    Schallig W, Veneman T, Noordhof DA, et al. The role of the rating-of-perceived-exertion template in pacing. Int J Sports Physiol Perform. 2018;13(3):367373. PubMed ID: 28771051 doi:10.1123/ijspp.2016-0813

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8.

    Liedl MA, Swain DP, Branch JD. Physiological effects of constant versus variable power during endurance cycling. Med Sci Sports Exerc. 1999;31(10):14721477. PubMed ID: 10527322 doi:10.1097/00005768-199910000-00018

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9.

    Thomas K, Stone MR, Thompson KG, Gibson ASC, Ansley L. The effect of self-even-and variable-pacing strategies on the physiological and perceptual response to cycling. Eur J Appl Physiol. 2012;112(8):30693078. PubMed ID: 22194003 doi:10.1007/s00421-011-2281-9

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10.

    Theurel J, Lepers R. Neuromuscular fatigue is greater following highly variable versus constant intensity endurance cycling. Eur J Appl Physiol. 2008;103(4):461468. PubMed ID: 18415118 doi:10.1007/s00421-008-0738-2

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11.

    Lepers R, Theurel J, Hausswirth C, Bernard T. Neuromuscular fatigue following constant versus variable-intensity endurance cycling in triathletes. J Sci Med Sport. 2008;11(4):381389. PubMed ID: 17499023 doi:10.1016/j.jsams.2007.03.001

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12.

    Coyle EF. Integration of the physiological factors determining endurance performance ability. Exerc Sport Sci Rev. 1995;23(1):2563. PubMed ID: 7556353 doi:10.1249/00003677-199500230-00004

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13.

    De Pauw K, Roelands B, Cheung SS, De Geus B, Rietjens G, Meeusen R. Guidelines to classify subject groups in sport-science research. Int J Sports Physiol Perform. 2013;8(2):111122. PubMed ID: 23428482 doi:10.1123/ijspp.8.2.111

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 14.

    Noordhof DA, Mulder RC, Malterer KR, Foster C, de Koning JJ. The decline in gross efficiency in relation to cycling time-trial length. Int J Sports Physiol Perform. 2015;10(1):6470. PubMed ID: 24911784 doi:10.1123/ijspp.2014-0034

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15.

    Abbiss C, Quod M, Levin G, Martin D, Laursen P. Accuracy of the Velotron ergometer and SRM power meter. Int J Sports Med. 2009;30(2):107112. PubMed ID: 19177315 doi:10.1055/s-0028-1103285

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16.

    Hermens HJ, Freriks B, Merletti R, et al. European recommendations for surface electromyography. Roessingh Res Dev. 1999;8(2):1354.

  • 17.

    Borg GA. Psychophysical bases of perceived exertion. Med Sci Sports Exerc. 1982;14(5):377381. PubMed ID: 7154893

  • 18.

    De CL. Myoelectrical manifestations of localized muscular fatigue in humans. Crit Rev Biomed Eng. 1984;11(4):251279. PubMed ID: 6391814

    • Search Google Scholar
    • Export Citation
  • 19.

    Kallenberg LA, Hermens HJ. Behaviour of a surface EMG based measure for motor control: motor unit action potential rate in relation to force and muscle fatigue. J Electromyogr Kines. 2008;18(5):780788. PubMed ID: 17466536 doi:10.1016/j.jelekin.2007.02.011

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 20.

    de Koning JJ, Noordhof DA, Uitslag TP, Galiart RE, Dodge C, Foster C. An approach to estimating gross efficiency during high-intensity exercise. Int J Sports Physiol Perform. 2013;8(6):682684. PubMed ID: 23006833 doi:10.1123/ijspp.8.6.682

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 21.

    Girden ER. ANOVA: Repeated Measures. Newbury Park, CA: Sage; 1992.

  • 22.

    Cohen J. Statistical Power Analysis for the Behavioral Sciences. New York, NY: Academic Press; 1988.

  • 23.

    Jung ME, Bourne JE, Little JP. Where does HIT fit? An examination of the affective response to high-intensity intervals in comparison to continuous moderate-and continuous vigorous-intensity exercise in the exercise intensity-affect continuum. PLoS One. 2014;9(12):e114541. PubMed ID: 25486273 doi:10.1371/journal.pone.0114541

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 24.

    Sandbrink F, Ellad C. Motor unit recruitment in EMG: definition of motor unit recruitment and overview. Medscape. Published 2016. Accessed January 21,  2020. https://emedicine.medscape. com/article/1141359-overview

    • Search Google Scholar
    • Export Citation
  • 25.

    Milner-Brown H, Stein R. The relation between the surface electromyogram and muscular force. J Physiol. 1975;246(3):549569. PubMed ID: 1133787 doi:10.1113/jphysiol.1975.sp010904

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26.

    Hettinga FJ, De Koning JJ, Broersen FT, Van Geffen P, Foster C. Pacing strategy and the occurrence of fatigue in 4000-m cycling time trials. Med Sci Sports Exerc. 2006;38(8):14841491. PubMed ID: 16888463 doi:10.1249/01.mss.0000228956.75344.91

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 27.

    Tucker R, Kayser B, Rae E, Rauch L, Bosch A, Noakes T. Hyperoxia improves 20 km cycling time trial performance by increasing muscle activation levels while perceived exertion stays the same. Eur J Appl Physiol. 2007;101(6):771781. PubMed ID: 17909845 doi:10.1007/s00421-007-0458-z

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 28.

    Rauch H, Gibson ASC, Lambert E, Noakes T. A signalling role for muscle glycogen in the regulation of pace during prolonged exercise. Br J Sport Med. 2005;39(1):3438. PubMed ID: 15618337 doi:10.1136/bjsm.2003.010645

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 29.

    Coyle EF, Coggan AR, Hopper M, Walters TJ. Determinants of endurance in well-trained cyclists. J Appl Physiol. 1988;64(6):26222630. PubMed ID: 3403447 doi:10.1152/jappl.1988.64.6.2622

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 30.

    Zimmerman BJ. Attaining self-regulation: A social cognitive perspective. In: Boekaerts M, Pintrich PR, Zeidner M, eds. Handbook of self-Regulation. San Diego, CA: Academic Press; 2000:1339.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 31.

    Levels K, de Koning JJ, Foster C, Daanen HA. The effect of skin temperature on performance during a 7.5-km cycling time trial. Eur J Appl Physiol. 2012;112(9):33873395. PubMed ID: 22270485 doi:10.1007/s00421-012-2316-x

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 1991 473 12
Full Text Views 92 38 2
PDF Downloads 84 9 0