Download PDF
Int J Sports Med 2017; 38(06): 456-461
DOI: 10.1055/s-0043-102945
Training & Testing
© Georg Thieme Verlag KG Stuttgart · New York

Accuracy of Cycling Power Meters against a Mathematical Model of Treadmill Cycling

Thomas Maier
1   Section for Elite Sport, Swiss Federal Institute of Sport, Magglingen, Switzerland
,
Lucas Schmid
1   Section for Elite Sport, Swiss Federal Institute of Sport, Magglingen, Switzerland
,
Beat Müller
1   Section for Elite Sport, Swiss Federal Institute of Sport, Magglingen, Switzerland
,
Thomas Steiner
1   Section for Elite Sport, Swiss Federal Institute of Sport, Magglingen, Switzerland
,
Jon Peter Wehrlin
1   Section for Elite Sport, Swiss Federal Institute of Sport, Magglingen, Switzerland
› Author Affiliations
Further Information

Publication History



accepted after revision 19 January 2017

Publication Date:
08 May 2017 (online)

Also available at
   Permissions and Reprints

Abstract

The aim of this study was to compare the accuracy among a high number of current mobile cycling power meters used by elite and recreational cyclists against a first principle-based mathematical model of treadmill cycling. 54 power meters from 9 manufacturers used by 32 cyclists were calibrated. While the cyclist coasted downhill on a motorised treadmill, a back-pulling system was adjusted to counter the downhill force. The system was then loaded 3 times with 4 different masses while the cyclist pedalled to keep his position. The mean deviation (trueness) to the model and coefficient of variation (precision) were analysed. The mean deviations of the power meters were –0.9±3.2% (mean±SD) with 6 power meters deviating by more than±5%. The coefficients of variation of the power meters were 1.2±0.9% (mean±SD), with Stages varying more than SRM (p<0.001) and PowerTap (p<0.001). In conclusion, current power meters used by elite and recreational cyclists vary considerably in their trueness; precision is generally high but differs between manufacturers. Calibrating and adjusting the trueness of every power meter against a first principle-based reference is advised for accurate measurements.

Key words

dynamic calibration - validity - reliability - measurement error
 

  • References

  • 1 Abbiss CR, Quod MJ, Levin G, Martin DT, Laursen PB. Accuracy of the velotron ergometer and SRM power meter. Int J Sports Med 2009; 30: 107-112
    Article in Thieme ConnectPubMedGoogle Scholar
  • 2 Atkinson G, Nevill AM. Selected issues in the design and analysis of sport performance research. J Sports Sci 2001; 19: 811-827
    CrossrefPubMedGoogle Scholar
  • 3 Bertucci W, Crequy S, Chiementin X. Validity and reliability of the G-cog BMX powermeter. Int J Sports Med 2013; 34: 538-543
    Article in Thieme ConnectPubMedGoogle Scholar
  • 4 Bertucci W, Duc S, Villerius V, Grappe F. Validity and reliability of the axiom PowerTrain cycle ergometer when compared with an SRM powermeter. Int J Sports Med 2005; 26: 59-65
    Article in Thieme ConnectPubMedGoogle Scholar
  • 5 Bertucci W, Duc S, Villerius V, Pernin JN, Grappe F. Validity and reliability of the PowerTap mobile cycling powermeter when compared with the SRM device. Int J Sports Med 2005; 26: 868-873
    Article in Thieme ConnectPubMedGoogle Scholar
  • 6 Coleman DA, Wiles JD, Davison RC, Smith MF, Swaine IL. Power output measurement during treadmill cycling. Int J Sports Med 2007; 28: 525-530
    Article in Thieme ConnectPubMedGoogle Scholar
  • 7 Di Prampero PE, Cortili G, Mognoni P, Saibene F. Equation of motion of a cyclist. J Appl Physiol 1979; 47: 201-206
    CrossrefPubMedGoogle Scholar
  • 8 Duc S, Villerius V, Bertucci W, Grappe F. Validity and reproducibility of the ErgomoPro power meter compared with the SRM and PowerTap power meters. Int J Sports Physiol Perform 2007; 2: 270-281
    CrossrefPubMedGoogle Scholar
  • 9 Gardner AS, Stephens S, Martin DT, Lawton E, Lee H, Jenkins D. Accuracy of SRM and PowerTap power monitoring systems for bicycling. Med Sci Sports Exerc 2004; 36: 1252-1258
    CrossrefPubMedGoogle Scholar
  • 10 Harriss DJ, Atkinson G. Ethical standards in sport and exercise science research: 2016 update. Int J Sports Med 2015; 36: 1121-1124
    Article in Thieme ConnectPubMedGoogle Scholar
  • 11 Henchoz Y, Crivelli G, Borrani F, Millet GP. A new method to measure rolling resistance in treadmill cycling. J Sports Sci 2010; 28: 1043-1046
    CrossrefPubMedGoogle Scholar
  • 12 Hopkins WG. Measures of reliability in sports medicine and science. Sports Med 2000; 30: 1-15
    CrossrefPubMedGoogle Scholar
  • 13 Hurst HT, Atkins S, Sinclair J, Metcalfe J. Agreement between the Stages cycling and SRM powermeter systems during field-based off-road climbing. J Sci Cycling 2015; 4: 21-27
    PubMedGoogle Scholar
  • 14 Jakeman P. A longitudinal study of exercise metabolism during recovery from viral illness. Br J Sports Med 1993; 27: 157-161
    CrossrefPubMedGoogle Scholar
  • 15 Jobson SA, Passfield L, Atkinson G, Barton G, Scarf P. The analysis and utilization of cycling training data. Sports Med 2009; 39: 833-844
    CrossrefPubMedGoogle Scholar
  • 16 Kirkland A, Coleman D, Wiles J, Hopker J. Validity and reliability of the Ergomo® pro powermeter. Int J Sports Med 2008; 29: 913-916
    Article in Thieme ConnectPubMedGoogle Scholar
  • 17 Lim AC, Homestead EP, Edwards AG, Carver TC, Kram R, Byrnes WC. Measuring changes in aerodynamic/rolling resistances by cycle-mounted power meters. Med Sci Sports Exerc 2011; 43: 853-860
    PubMedGoogle Scholar
  • 18 Martin JC, Milliken DL, Cobb JE, McFadden KL, Coggan AR. Validation of a mathematical model for road cycling power. J Appl Biomech 1998; 14: 276-291
    PubMedGoogle Scholar
  • 19 Maxwell BF, Withers RT, Ilsley AH, Wakim MJ, Woods GF, Day L. Dynamic calibration of mechanically, air- and electromagnetically braked cycle ergometers. Eur J Appl Physiol 1998; 78: 346-352
    CrossrefPubMedGoogle Scholar
  • 20 Miller MC, Macdermid PW, Fink PW, Stannard SR. Agreement between PowerTap, Quarq and Stages power meters for cross-country mountain biking. Sports Technol 2016 Epub ahead of print: 1–7
    PubMed
  • 21 Olds TS, Norton KI, Lowe EL, Olive S, Reay F, Ly S. Modeling road-cycling performance. J Appl Physiol 1995; 78: 1596-1611
    CrossrefPubMedGoogle Scholar
  • 22 Quod MJ, Martin DT, Martin JC, Laursen PB. The power profile predicts road cycling MMP. Int J Sports Med 2010; 31: 397-401
    Article in Thieme ConnectPubMedGoogle Scholar
  • 23 Sparks SA, Dove B, Bridge CA, Midgely AW, McNaughton LR. Validity and reliability of the look Keo power pedal system for measuring power output during incremental and repeated sprint cycling. Int J Sports Physiol Perform 2015; 10: 39-45
    CrossrefPubMedGoogle Scholar
  • 24 Spicer JB, Richardson CJK, Ehrlich MJ, Bernstein JR, Fukuda M, Terada M. Effects of frictional loss on bicycle chain drive efficiency. J Mech Des 2001; 123: 598-605
    CrossrefPubMedGoogle Scholar
  • 25 Stein ES, Rothstein MS, Clements Jr CJ. Calibration of two bicycle ergometers used by the health examination survey. Vital Health Stat 2 1967; 1-10
    PubMedGoogle Scholar
  • 26 Vogt S, Schumacher YO, Roecker K, Dickhuth HH, Schoberer U, Schmid A, Heinrich L. Power output during the Tour de France. Int J Sports Med 2007; 28: 756-761
    Article in Thieme ConnectPubMedGoogle Scholar
  • 27 Woods GF, Day L, Withers RT, Ilsley AH, Maxwell BF. The dynamic calibration of cycle ergometers. Int J Sports Med 1994; 15: 168-171
    Article in Thieme ConnectPubMedGoogle Scholar