Dynamic calibration of mechanically, air- and electromagnetically braked cycle ergometers

In this study we measured the accuracy of the following types of cycle ergometer against the criterion of a dynamic calibration rig (DCR): 35 friction-braked (Monark), 5 research-grade air-braked (Repco) and 5 electromagnetically braked (2 Siemens, 1 Elema-Schonander, 1 Ergoline, l Warren E. Collins). Monark ergometer power outputs over the range 58.9–353.2 W significantly (P < 0.001) underestimated those registered by the DCR with mean accuracies of 91.7–97.8%. The least accurate individual reading for each of the six up-scale (0–353.2 W) power outputs ranged from 81.6␣to␣91.6%; corresponding down-scale (353.2–0 W) accuracies were 85.1–92.5%. A hysteresis effect was furthermore evident for this ergometer in that up-scale measurements were significantly (P < 0.05) greater than down-scale ones. In addition, when the oldest [mean (SD): 11.3 (2.3) years old] and newest [1.4 (0.8) years old] eight ergometers were compared, the latter were significantly (P < 0.05) more accurate over the range 117.7–294.3 W. Apart from the two lowest power outputs of 47␣W (62.2–96.0% accuracy) and 127 W (88.0–97.7% accuracy), the individual up-scale and down-scale accuracies of the Repco ergometers ranged from 98.0 to 104.2% for power outputs of 272.7–1137.8 W and the means were not significantly different from those of the DCR. There was also no evidence of hysteresis. Except for the initial power output of 50 W (40 rev/min: 83.8–99.2% accuracy; 60 rev/min: 93.2–122.6% accuracy), the␣individual accuracies of the electromagnetically braked ergometers ranged from 89.3 to 101.4% over the up-scale range of 100–400 W, and none of the means were significantly different from those of the DCR. The variability of individual errors for the preceding data emphasises that all cycle ergometers should be validated against the criterion of a DCR if accurate power outputs are required. Accepted: 19 February 1998     

Force platforms as ergometers.

Walking and running on the level involves external mechanical work, even when speed averaged over a complete stride remains constant. This work must be performed by the muscles to accelerate and/or raise the center of mass of the body during parts of the stride, replacing energy which is lost as the body slows and/or falls during other parts of the stride. External work can be measured with fair approximation by means of a force plate, which records the horizontal and vertical components of the resultant force applied by the body to the ground over a complete stride. The horizontal force and the vertical force minus the body weight are integrated electronically to determine the instantaneous velocity in each plane. These velocities are squared and multiplied by one-half the mass to yield the instantaneous kinetic energy. The change in potential energy is calculated by integrating vertical velocity as a function of time to yield vertical displacement and multiplying this by body weight. The total mechanical energy as a function of time is obtained by adding the instantaneous kinetic and potential energies. The positive external mechanical work is obtained by adding the increments in total mechanical energy over an integral number of strides.     

Reliability and validity of the modified Conconi test on concept II rowing ergometers

The purpose of this study was to assess the reliability and validity of the modified Conconi test on Concept II rowing ergometers. Twenty-eight oarsmen conducted 3 performance tests on separate days. Reliability was assessed using the break point in heart rate (HR) linearity called the Conconi test (CT) and Conconi retest (CRT) for the noninvasive measurement of anaerobic threshold (AT). Blood lactate measurement was considered the gold standard for the assessment of the AT, and the validity of the CT was assessed by blood samples taken during an incremental load test (ILT) on ergometers. According to the results, the mean power output (PO) scores for the CT, CRT, and ILT were 234.2 +/- 40.3 W, 232.5 +/- 39.7 W, and 229.7 +/- 39.6 W, respectively. The mean HR values at the AT for the CT, CRT, and ILT were 165.4 +/- 11.2 b.min, 160.4 +/- 10.8 b.min, and 158.3 +/- 8.8 b.min, respectively. Interclass correlation coefficient (ICC) analysis indicated a significant correlation between the 3 tests with one another. Also, Bland and Altman plots showed that there was an association between noninvasive tests and the ILT PO scores and HRs (95% confidence interval [CI]). In conclusion, this study showed that the modified CT is a reliable and valid method for determining the AT of elite men rowers.     

Analysis of EMG measurements during bicycle pedalling

Activity of eight leg muscles has been monitored for six test subjects while pedalling a bicycle on rollers in the laboratory. Each electromyogram (EMG) data channel was digitized at a sampling rate of 2 kHz by a minicomputer. Data analysis entailed generating plots of both EMG activity regions and integrated EMG (IEMG). For each test subject, data were recorded for five cases of pedalling conditions. The different pedalling conditions were defined to explore a variety of research hypotheses. This exploration has led to the following conclusions: Muscular activity levels of the quadriceps are influenced by the type of shoes worn and activity levels increase with soft sole shoes as opposed to cycling shoes with cleats and toeclips. EMG activity patterns are not strongly related to pedalling conditions (i.e. load, seat height and shoe type). The level of muscle activity, however, is significantly affected by pedalling conditions. Muscular activity bears a complex relationship with seat height and quadriceps activity level decreases with greater seat height. Agonist (i.e. hamstrings) and antagonist (i.e. quadriceps) muscles of the hip/knee are active simultaneously during leg extension. Regions of peak activity levels, however, do not overlap. The lack of significant cocontraction of agonist/antagonist muscles enables muscle forces during pedalling action to be computed by solving a series of equilibrium problems over different regions of the crank cycle. Regions are defined and a solution procedure is outlined.     

Determinants of bicycle commuting and the effect of bicycle infrastructure investment in London: Evidence from UK census microdata

Worldwide, concern about physical inactivity and excessive car dependence has encouraged ambitious targets and policies to promote cycling. But policy making is hindered by limited knowledge about why cycling prevalence and trends vary greatly between different geographic areas (e.g. in London (UK) <1% cycle to work in Harrow compared to>15 % in Hackney) and individuals (e.g. by age or gender). The role of cycle infrastructure investment in explaining part of these patterns and trends is also unknown. We linked individual-level data on 317,117 London commuters (including 11,199 cyclists) in the 2001 and 2011 UK census to relevant geographic data, including on area-level cycling infrastructure investment during the period. Whilst cycle commuting increased over time on average, concentration curves and indices demonstrated that in contrast with England as a whole, cycling in London shifted from being dominated by commuters with lower socioeconomic status to commuters with higher socioeconomic status. In our first set of regression analyses, we showed that observed differences and time trends in cycling prevalence were partially explained by area-level differences in topography, greenspace, footpaths and crime levels and by differences and changes in population structures. In the second, we conducted a cost-effectiveness analysis which showed that expenditure on cycling infrastructure was associated with increased cycling at a marginal rate of £4915 per additional commuter cyclist, with some variation between groups: ethnic minorities were more responsive, and females, older people and those with lower socioeconomic status appeared less responsive. If planned increases in expenditure in England for the period 2020−25 were as cost-effective, and were sustained for the whole decade, our study suggests that commuter cycling prevalence could increase in England by 0.5 to 1.1 percentage points (this equates to a 16% to 34% increase in commuter cycling prevalence if compared to 2011 levels). More research is necessary to assess the impact on broader measures of cycling, active travel and overall physical activity, and to determine whether such expenditure constitutes good or equitable value for money.