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# Time to exhaustion during cycling is not well predicted by critical power calculations

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## Abstract

Three to 5 cycling tests to exhaustion allow prediction of time to exhaustion (TTE) at power output based on calculation of critical power (CP). We aimed to determine the accuracy of CP predictions of TTE at power outputs habitually endured by cyclists. Fourteen endurance-trained male cyclists underwent 4 randomized cycle-ergometer TTE tests at power outputs eliciting (i) mean Wingate anaerobic test (WAnT mean ), (ii) maximal oxygen consumption, (iii) respiratory compensation threshold (VT 2 ), and (iv) maximal lactate steady state (MLSS). Tests were conducted in duplicate with coefficient of variation of 5%–9%. Power outputs were 710 ± 63 W for WAnT mean , 366 ± 26 W for maximal oxygen consumption, 302 ± 31 W for VT 2 and 247 ± 20 W for MLSS. Corresponding TTE were 00:29 ± 00:06, 03:23 ± 00:45, 11:29 ± 05:07, and 76:05 ± 13:53 min:s, respectively. Power output associated with CP was only 2% lower than MLSS (242 ± 19 vs. 247 ± 20 W; P < 0.001). The CP predictions overestimated TTE at WAnT mean (00:24 ± 00:10 mm:ss) and MLSS (04:41 ± 11:47 min:s), underestimated TTE at VT 2 (–04:18 ± 03:20 mm:ss; P < 0.05), and correctly predicted TTE at maximal oxygen consumption. In summary, CP accurately predicts MLSS power output and TTE at maximal oxygen consumption. However, it should not be used to estimate time to exhaustion in trained cyclists at higher or lower power outputs (e.g., sprints and 40-km time trials). Novelty CP calculation enables to predict TTE at any cycling power output. We tested those predictions against measured TTE in a wide range of cycling power outputs. CP appropriately predicted TTE at maximal oxygen consumption intensity but err at higher and lower cycling power outputs.

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... Consequently, nominal 'all-out' efforts are (aside from the omnipresent issue of motivation, see below) subject to variability due to individual pacing choice and fluctuations. With the advent of electromagnetically braked cycle ergometers, it has become much easier to employ constant work rates (CWR) (e.g., McLellan et al. 1995;Muniz-Pumares et al. 2017;Pallarés et al. 2020;Vanhatalo et al. 2011), or self-paced, time-trialtype efforts (Denadai et al. 2005;Garatachea et al. 2006;Kordi et al. 2021;Lillo-Beviá et al. 2022). Importantly, self-paced trials typically produce greater mean power outputs (or velocities) and thus higher CP values. ...
... Beyond the already cited examples of the differential effect of short vs. long trials, and those first summarized by DW Hill (1993), the reported data of two different sample studies vividly demonstrate that observed deviations from linearity are much more fundamental than mere experimental errors. With one trial deep in the 'exclusion zone', Pallarés et al. (2020) had 14 endurance-trained cyclists complete 4 maximal efforts of 28, 203, 684, and 4446s (~0.5-74 min, 710-247 W, respectively) (Fig. 5). The intercept of the 4-point P-1/t linear regression indicates CP of 276.6 W, but it is glaringly apparent (Fig. 5A) that these 4 points do not reside on a linear relationship and that linearity would not attained even had the shortest trial been omitted. ...
... The Pallarés et al. (2020) study (discussed earlier under 'Pseudo Linearity') found CP to be practically identical to MLSS (indeed, 0.4% lower). The study is an excellent example of the subduing effect long trials have on CP. ...
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The elegant concept of a hyperbolic relationship between power, velocity, or torque and time to exhaustion has rightfully captivated the imagination and inspired extensive research for over half a century. Theoretically, the relationship’s asymptote along the time axis (critical power, velocity, or torque) indicates the exercise intensity that could be maintained for extended durations, or the “heavy–severe exercise boundary”. Much more than a critical mass of the extensive accumulated evidence, however, has persistently shown the determined intensity of critical power and its variants as being too high to maintain for extended periods. The extensive scientific research devoted to the topic has almost exclusively centered around its relationships with various endurance parameters and performances, as well as the identification of procedural problems and how to mitigate them. The prevalent underlying premise has been that the observed discrepancies are mainly due to experimental ‘noise’ and procedural inconsistencies. Consequently, little or no effort has been directed at other perspectives such as trying to elucidate physiological reasons that possibly underly and account for those discrepancies. This review, therefore, will attempt to offer a new such perspective and point out the discrepancies’ likely root causes.
... The RCP has also been suggested as a landmark of the boundary between heavy and very heavy exercise domains [4]. Different studies have assessed the tlim at the PO corresponding to a key endurance fitness indicator, the peak oxygen uptake (VO2peak), yielding tlim values of ~3-4 min [12,13]. However, scarce evidence is available regarding the tlim at the PO corresponding to the RCP (herein simply 'tlim at RCP') and whether a steady physiological state is observed at this workload. ...
... A convenience sample of sixty healthy male recreational cyclists participated in this study (Table 1). This sample size was considered sufficient as other studies assessing the tlim have included a lower number of participants (i.e., n = 14 [12] and n = 41 [13]). Participants were free of any disease (e.g., diabetes, asthma) and were not taking any medication. ...
... To the best of our knowledge, only two studies have previously estimated the tlim at RCP. Bergstrom et al. inferred a tlim value for PO@RCP of ~11 min based on power curve analyses in eight moderately-trained participants [17]. More recently, Pallarés et al. also reported a tlim of ~11 min at the RCP determined using a similar incremental test to that used here (25 W•min −1 ) [12]. Thus, the tlim at RCP observed in the present study for recreational cyclists of different fitness levels seems to be greater than those reported in previous studies for trained individuals. ...
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The time to exhaustion (tlim) at the respiratory compensation point (RCP) and whether a physiological steady state is observed at this workload remains unknown. Thus, this study analyzed tlim at the power output eliciting the RCP (tlim at RCP), the oxygen uptake (VO2) response to this effort, and the influence of endurance fitness. Sixty male recreational cyclists (peak oxygen uptake [VO2peak] 40-60 mL•kg•min −1) performed an incremental test to determine the RCP, VO2peak, and maximal aerobic power (MAP). They also performed constant-load tests to determine the tlim at RCP and tlim at MAP. Participants were divided based on their VO2peak into a low-performance group (LP, n = 30) and a high-performance group (HP, n = 30). The tlim at RCP averaged 20 min 32 s ± 5 min 42 s, with a high between-subject variability (coefficient of variation 28%) but with no differences between groups (p = 0.788, effect size = 0.06). No consistent relationships were found between the tlim at RCP and the different fitness markers analyzed (RCP, power output (PO) at RCP, VO2peak, MAP, or tlim at MAP; all p > 0.05). VO2 remained steady overall during the tlim test, although a VO2 slow component (i.e., an increase in VO2 >200 mL•min −1 from the third min to the end of the tests) was present in 33% and 40% of the participants in HP and LP, respectively. In summary, the PO at RCP could be maintained for about 20 min. However, there was a high between-subject variability in both the tlim and in the VO2 response to this effort that seemed to be independent of fitness level, which raises concerns on the suitability of this test for fitness assessment.
... Rescuer interventions in a life-threatening emergency require a 3-12 min vigorous and stressful effort at intensities higher than the ventilatory threshold and up to the maximum oxygen consumption mark [17,18]. However, some efforts are shorter than 1 min, relying heavily on anaerobic energy since there was not sufficient time for recruiting aerobic energy (with maximum heart rate and maximum cardiac output being obtained latter) [17,19,20]. ...
... Rescuer interventions in a life-threatening emergency require a 3-12 min vigorous and stressful effort at intensities higher than the ventilatory threshold and up to the maximum oxygen consumption mark [17,18]. However, some efforts are shorter than 1 min, relying heavily on anaerobic energy since there was not sufficient time for recruiting aerobic energy (with maximum heart rate and maximum cardiac output being obtained latter) [17,19,20]. The influence of a typical 100 m maximal run on emergency medical technicians CPR manoeuvres has already been studied [1], but the fatigue effect of different locomotion modes on CPR quality is not sufficiently well addressed. ...
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... These time-shortened protocols measure the power output produced in the first seconds of the test, such as the peak power output (PPO) or power value generated at specific time points (e.g., at the second 10 or 15), to predict other performance parameters like the mean power (MPO) by means of regression analyses [6,9,11]. MPO is considered a variable of interest in many investigations [13,14], since it could be predictive of the anaerobic capacity (i.e., ability to sustain extremely high power) [1,2,15]. Another key variable derived from a WAnT is the fatigue index (FI). ...
... Thus, instantaneous power output could be obtained by means of the simultaneous measure of the angular velocity. This methodology has been previously used to measure power output changes after different training programs [13,14] and evaluate the force-velocity profile in cycling [22]. However, no study to date has analyzed a time-shortened WAnT using this technology. ...
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This study aimed to analyze the validity and sensitivity of two time-shortened Wingate anaerobic tests (WAnTs), by means of three phases. In Phase A, 40 participants performed a traditional 30 s WAnT, whereas the first 15 s (WAnT15) and 20 s (WAnT20) were used to elaborate two predictive models. In Phase B, another 30 s WAnT was performed by 15 different volunteers to examine the error of these models (cross-validation). Finally, in Phase C, a 30 s WAnT was registered before and after a 10-week velocity-based training conducted by 22 different participants (training group, TRAIN = 11; control group that fully refrained from any type of training, CONTROL = 11). Power changes (in Watts, W) after this training intervention were used to interpret the sensitivity of the time-shortened WAnT. Adjusted coefficient of determination (R2) was reported for each regression model, whereas the cross-validation analysis included the smallest detectable change (SDC) and bias. Close relationships were found between the traditional 30 s WAnT and both the WAnT15 (R2 = 0.98) and WAnT20 (R2 = 0.99). Cross-validation analysis showed a lower error and bias for WAnT20 (SDC = 9.3 W, bias = −0.1 W) compared to WAnT15 (SDC = 22.2 W, bias = 1.8 W). Lastly, sensitivity to identify individual changes was higher for WAnT20 (TRAIN = 11/11 subjects, CONTROL = 9/11 subjects) than for WAnT15 (TRAIN = 4/11 subjects, CONTROL = 2/11 subjects). These findings suggest that the WAnT20 could become a valid and sensitive protocol to replace the traditional 30 s WAnT.
... Despite the use of power meters, training management software and high-quality indoor cycle training equipment, there was an overall loss in functional performance of about 9% in P5 and 12% in P20, surrogates of theVO 2 max; and maximum lactate steady state, respectively. 10,11 These decreases are likely to be attributable to the severe reduction, by one-third, in the weekly training volume, (mean difference 95% CI, −4 to −8 h·wk −1 ). In particular, training volumes at low-intensities (Z1), at threshold (Z4), and high-intensities (Z5 and Z6) showed the biggest decline with 40% to 52% loss. ...
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Abstract The maximal lactate steady state (MLSS) and the critical power (CP) are two widely used indices of the highest oxidative metabolic rate that can be sustained during continuous exercise and are often considered to be synonymous. However, while perhaps having similarities in principle, methodological differences in the assessment of these parameters typically result in MLSS occurring at a somewhat lower power output or running speed and exercise at CP being sustainable for no more than approximately 20–30 min. This has led to the view that CP overestimates the ‘actual’ maximal metabolic steady state and that MLSS should be considered the ‘gold standard’ metric for the evaluation of endurance exercise capacity. In this article we will present evidence consistent with the contrary conclusion: i.e., that (1) as presently defined, MLSS naturally underestimates the actual maximal metabolic steady state; and (2) CP alone represents the boundary between discrete exercise intensity domains within which the dynamic cardiorespiratory and muscle metabolic responses to exercise differ profoundly. While both MLSS and CP may have relevance for athletic training and performance, we urge that the distinction between the two concepts/metrics be better appreciated and that comparisons between MLSS and CP, undertaken in the mistaken belief that they are theoretically synonymous, is discontinued. CP represents the genuine boundary separating exercise in which physiological homeostasis can be maintained from exercise in which it cannot, and should be considered the gold standard when the goal is to determine the maximal metabolic steady state.
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Purpose The three-parameter model of critical power (3-p) implies that in the severe exercise intensity domain time to exhaustion (Tlim) decreases hyperbolically with power output starting from the power asymptote (critical power, ẇcr) and reaching 0 s at a finite power limit (ẇ0) thanks to a negative time asymptote (k). We aimed to validate 3-p for short Tlim and to test the hypothesis that ẇ0 represents the maximal instantaneous muscular power. Methods Ten subjects performed an incremental test and nine constant-power trials to exhaustion on an electronically braked cycle ergometer. All trials were fitted to 3-p by means of non-linear regression, and those with Tlim greater than 2 min also to the 2-parameter model (2-p), obtained constraining k to 0 s. Five vertical squat jumps on a force platform were also performed to determine the single-leg (i.e., halved) maximal instantaneous power. Results Tlim ranged from 26 ± 4 s to 15.7 ± 4.9 min. In 3-p, with respect to 2-p, ẇcr was identical (177 ± 26 W), while curvature constant W’ was higher (17.0 ± 4.3 vs 15.9 ± 4.2 kJ, p < 0.01). 3-p-derived ẇ0 was lower than single-leg maximal instantaneous power (1184 ± 265 vs 1554 ± 235 W, p < 0.01). Conclusions 3-p is a good descriptor of the work capacity above ẇcr up to Tlim as short as 20 s. However, since there is a discrepancy between estimated ẇ0 and measured maximal instantaneous power, a modification of the model has been proposed.
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Critical power (CP) and the second ventilatory threshold (VT(2)) are presumed to indicate the power corresponding to maximal lactate steady state (MLSS). The aim of this study was to investigate the use of CP and VT(2) as indicators of MLSS. Eleven male trained subjects [mean (SD) age 23 (2.9) years] performed an incremental test (25 W.min(-1)) to determine maximal oxygen uptake (.VO(2max)), maximal aerobic power (MAP) and the first and second ventilatory thresholds (VT(1) and VT(2)) associated with break points in minute ventilation (.V(E)), carbon dioxide production (.VCO(2)), .V(E)/.VCO(2) and .V(E)/.VO(2) relationships. Exhaustion tests at 90%, 95%, 100% and 110% of .VO(2max), and several 30-min constant work rates were performed in order to determine CP and MLSS, respectively. MAP and .VO(2max) values were 344 (29) W and 53.4 (3.7) ml.min(-1).kg(-1), respectively. CP [278 (22) W; 85.4 (4.8)% .VO(2max)] and VT(2) power output [286 (28) W; 85.3 (5.6)% .VO(2max)] were not significantly different (p=0.96) but were higher (p<0.05) than the MLSS work rate [239 (21) W; 74.3 (4.0)% .VO(2max)] and VT(1) power output [159 (23) W; 52.9 (6.9)% .VO(2max)]. MLSS work rate was significantly correlated (p<0.05) with those noted at VT(1) and VT(2) (r=0.74 and r=0.93, respectively). VT(2) overestimated MLSS by 10.9 (6.3)% .VO(2max), which was significantly higher than VT(1) [+21.4 (5.6)% .VO(2max); p<0.01]. CP calculated from a given range of exhaustion times does not correspond to MLSS.
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This study compared running velocity, physiological responses, and perceived exertion during self-paced interval training bouts differing only in work bout duration. Twelve well-trained runners (nine males, three females, 28+/-5 years, VO2 max 65+/-6 mL min(-1) kg(-1)) performed preliminary testing followed by four "high-intensity" interval sessions (Latin squares, 1 session week(-1) over 4 weeks) consisting of 24 x 1, 12 x 2, 6 x 4, or 4 x 6-min running bouts with a 1:1 work-to-rest interval (total session duration 48 min). The average running velocity decreased (93%, 88%, 86%, 84% vVO2 max, P < 0.01) with increasing work duration. Peak VO2 averaged about 92+/-4% of VO2 max for 2-, 4-, and 6-min intervals compared with only 82+/-5% for 1-min bouts (P < 0.001). Six of 12 athletes achieved their highest average VO2 and heart rate during 4-min intervals. The average RPEpeak (rating scale of perceived exertion) was approximately 17+/-1 for all four interval sessions. RPE increased by 2-4 U during an interval training session. The mean lactate concentration was similar across sessions (4.3+/-1.1-4.6+/-1.5 mmol L(-1)). Under self-paced conditions, well-trained runners perform "high-intensity" intervals at an RPE of approximately 17, independent of interval duration. The optimal interval duration for eliciting a high physiological load is 3-5 min under these training conditions. Increases in RPE during an interval bout are not associated with increasing blood lactate concentration.
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Lillo-Beviá, JR, Courel-Ibáñez, J, Cerezuela-Espejo, V, Morán-Navarro, R, Martínez-Cava, A, and Pallarés, JG. Is the functional threshold power a valid metric to estimate the maximal lactate steady state in cyclists? J Strength Cond Res XX(X): 000-000, 2019-The aims of this study were to determine (a) the repeatability of a 20-minute time-trial (TT20), (b) the location of the TT20 in relation to the main physiological events of the aerobic-anaerobic transition, and (c) the predictive power of a list of correction factors and linear/multiple regression analysis applied to the TT20 result to estimate the individual maximal lactate steady state (MLSS). Under laboratory conditions, 11 trained male cyclists and triathletes (V[Combining Dot Above]O2max 59.7 ± 3.0 ml·kg·min) completed a maximal graded exercise test to record the power output associated with the first and second ventilatory thresholds and V[Combining Dot Above]O2max measured by indirect calorimetry, several 30 minutes constant tests to determine the MLSS, and 2 TT20 tests with a short warm-up. Very high repeatability of TT20 tests was confirmed (standard error of measurement of ±3 W and smallest detectable change of ±9 W). Validity results revealed that MLSS differed substantially from TT20 (bias = 26 ± 7 W). The maximal lactate steady state was then estimated from the traditional 95% factor (bias = 12 ± 7 W) and a novel individual correction factor (ICF% = MLSS/TT20), resulting in 91% (bias = 1 ± 6 W). Complementary linear (MLSS = 0.7488 × TT20 + 43.24; bias = 0 ± 5 W) and multiple regression analysis (bias = 0 ± 4 W) substantially improved the individual MLSS workload estimation. These findings suggest reconsidering the TT20 procedures and calculations to increase the effectiveness of the MLSS prediction.
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The dissociation between constant-work rate V̇O 2 and ramp-V̇O 2 at a given work rate might be mitigated during slow increasing ramp-protocols. This study characterized the V̇O 2 dynamics in response to five different ramp-protocols and constant-work rate trials at the maximal metabolic steady-state (MMSS), to characterize i) the V̇O 2 gain (G) in the moderate, heavy, and severe domains, ii) the mean response time of V̇O 2 (MRT), iii) the work rates at lactate threshold (LT) and respiratory compensation-point (RCP). Eleven young individuals performed five ramp-tests (5, 10, 15, 25, 30 W·min ⁻¹ ), 4-5 time-to-exhaustions for critical power estimation, and 2-3 constant-work rate trials for confirmation of the work rate at MMSS. G was greatest during the slowest ramp, and progressively decreased with increasing ramp-slopes (from ~12 to ~8 ml·min ⁻¹ ·W ⁻¹ ) ( P<0.05). The MRT was smallest during the slowest ramp-slopes and progressively increased with faster ramp-slopes (1±1, 2±1, 5±3, 10±4, 15±6 W, P<0.05). After "left-shifting" the ramp-V̇O 2 by the MRT, the work rate at LT was constant regardless of the ramp-slope (~150W) ( P>0.05). The work rate at MMSS was 215±55W and was similar and high correlated with the work rate at RCP during the 5 W·min ⁻¹ ramp ( P>0.05) (r = 0.99; CCC = 0.99; bias = -3 W; RMSE = 6W). Findings showed that the dynamics of V̇O 2 (i.e., G) during ramp-exercise explain the apparent dichotomy existing with constant-work rate exercise. When these dynamics are appropriately "resolved", LT is constant regardless of the ramp-slope of choice and RCP and MMSS display minimal variations between each other.
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Common methods to prescribe exercise intensity are based on fixed-percentages of maximum rate of oxygen uptake (V[Combining Dot Above]O2max), peak work rate (WRpeak), maximal heart rate (HRmax). However, it is unknown how these methods compare to the current models to partition the exercise intensity spectrum. Purpose: Thus, the aim of this study was to compare contemporary gold-standard approaches for exercise prescription based on fixed-percentages of maximum values to the well established but underutilized "domain" schema of exercise intensity. Methods: One hundred individuals participated in the study (women=46; men=54). A cardiopulmonary ramp-incremental test was performed to assess V[Combining Dot Above]O2max, WRpeak, HRmax, and the lactate threshold (LT), and submaximal constant-work rate trials of 30-min duration to determine the maximal lactate steady-state (MLSS). The LT and MLSS were used to partition the intensity spectrum for each individual in three domains of intensity: moderate, heavy, and severe. Results: V[Combining Dot Above]O2max in women and men was 3.06±0.41 L·min and 4.10±0.56 L·min, respectively. LT and MLSS occurred at a greater %V[Combining Dot Above]O2max and %HRmax in women compared to men (P<0.05). The large ranges in both sexes at which LT and MLSS occurred on the basis of %V[Combining Dot Above]O2max (LT=45-74%; MLSS=69-96%), %WRpeak (LT=23-57%; MLSS=44-71%), and %HRmax (LT=60-90%; MLSS=75-97%) elicited large variability in the number of individuals distributed in each domain at the fixed-percentages examined. Conclusions: Contemporary gold-standard methods for exercise prescription based on fixed-percentages of maximum values conform poorly to exercise intensity domains and thus do not adequately control the metabolic stimulus.
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It is not clear how the parameters of the power-duration relationship [critical power (CP) and W'] are influenced by the performance of prolonged endurance exercise. We used severe-intensity prediction trials (conventional protocol) and the 3-min all-out test (3MT) to measure CP and W' following 2 h of heavy-intensity cycling exercise and took muscle biopsies to investigate possible relationships to changes in muscle glycogen concentration ([glycogen]). Fourteen participants completed a rested 3MT to establish end-test power (Control-EP) and work done above EP (Control-WEP). Subsequently, on separate days, immediately following 2 h of heavy-intensity exercise, participants completed a 3MT to establish Fatigued-EP and Fatigued-WEP and three severe-intensity prediction trials to the limit of tolerance (Tlim) to establish Fatigued-CP and Fatigued-W'. A muscle biopsy was collected immediately before and after one of the 2-h exercise bouts. Fatigued-CP (256 ± 41 W) and Fatigued-EP (256 ± 52 W), and Fatigued-W' (15.3 ± 5.0 kJ) and Fatigued-WEP (14.6 ± 5.3 kJ), were not different (P > 0.05) but were ~11% and ~20% lower than Control-EP (287 ± 46 W) and Control-WEP (18.7 ± 4.7 kJ), respectively (P < 0.05). The change in muscle [glycogen] was not significantly correlated with the changes in either EP (r = 0.19) or WEP (r = 0.07). The power-duration relationship is adversely impacted by prolonged endurance exercise. The 3MT provides valid estimates of CP and W' following 2 h of heavy-intensity exercise, but the changes in these parameters are not primarily determined by changes in muscle [glycogen].
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During ramp-incremental exercise, the mean response time (MRT) of oxygen uptake (V˙O2) represents the time delay for changes in muscle V˙O2 to be reflected at the level of the mouth and is generally calculated by linear (MRTLIN) and monoexponential (τ') fitting of V˙O2 data. However, these methods yield MRT values that are highly variable from test-to-test. Purpose: Therefore, we examined the validity and the reproducibility of a novel method to calculate the MRT. Methods: On two occasions, 12 healthy men (age, 30 ± 10 yr; V˙O2max: 4.14 ± 0.47 L·min, 53.5 ± 7.3 mL·kg·min) performed a ramp-incremental cycling test (30 W·min) that was preceded by a step transition to 100 W. The ramp power output corresponding to the steady-state V˙O2 at 100 W was determined and the difference between that power output and 100 W was converted to time to quantify the MRT (MRTSS). Results: The values of MRTLIN, τ', and MRTSS were 28 ± 16 s, 27 ± 12 s, and 26 ± 11 s, respectively, which were not different (P > 0.05) from each other. However, compared to the MRT parameters derived from the fitting-based methods, MRTSS had a higher correlation coefficient (R = 0.87) and a smaller coefficient of variation (15% ± 9%) from test-to-test. Conclusions: In conclusion, the novel method proposed in the current study was found to be valid and highly reproducible in a test-retest design. Therefore, we advocate the use of this approach when a precise and accurate determination of the MRT is needed to properly align the V˙O2 data with power output during ramp-incremental exercise.
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The relationship between exercise intensity and time to task failure (P-T relationship) is hyperbolic, and characterized by its asymptote (critical power[CP]) and curvature constant (W'). The determination of these parameters is of interest for researchers and practitioners, but the testing protocol for CP and W' determination has not yet been standardized. Conventionally, a series of constant work rate (CWR) tests to task failure have been used to construct the P-T relationship. However, the duration, number, and recovery between predictive CWR and the mathematical model (hyperbolic or derived linear models) are known to affect CP and W'. Moreover, repeating CWR may be deemed as a cumbersome and impractical protocol. Recently, CP and W' have been determined in field and laboratory settings using time trials, but the validity of these methods has raised concerns. Alternatively, a 3-minute all-out test (3MT) has been suggested, as it provides a simpler method for the determination of CP and W', whereby power output at the end of the test represents CP, and the amount of work performed above this end-test power equates to W'. However, the 3MT still requires an initial incremental test and may overestimate CP. The aim of this review is, therefore, to appraise current methods to estimate CP and W', providing guidelines and suggestions for future research where appropriate.
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Despite compelling evidence to the contrary, the view that oxygen uptake (V̇O2) increases linearly with exercise intensity (e.g. power output, speed) until reaching its maximum (V̇O2max) persists within the exercise physiology literature. This viewpoint implies that the V̇O2 response at any constant-intensity is predictable from a ramp-incremental exercise test. However, the V̇O2 versus task-specific exercise intensity relationship constructed from ramp-incremental versus constant-intensity exercise are not equivalent preventing the use of V̇O2 responses from one domain to predict those of the other. Still, this "linear" translational framework continues to be adopted as the guiding principle for aerobic exercise prescription and there remains in the sport science literature a lack of understanding of how to interpret V̇O2 responses to ramp-incremental exercise and how to use those data to assign task-specific constant-intensity exercise. The objectives of this paper are to: 1) review the factors that disassociate the V̇O2 versus exercise intensity relationship between ramp-incremental and constant-intensity exercise paradigms; 2) identify when it is appropriate (or not) to use ramp V̇O2 responses to accurately assign constant-intensity exercise; and 3) illustrate the technical and theoretical challenges with prescribing constant-intensity exercise solely on information acquired from ramp-incremental tests. Actual V̇O2 data collected during cycling exercise and V̇O2 kinetics modelling are presented to exemplify these concepts. Possible solutions to overcome these challenges are also presented to inform on appropriate intensity selection for individual-specific aerobic exercise prescription in both research and practical settings.
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In cycling, critical power (CP) and work above CP (W’) can be estimated through linear and nonlinear models. Despite the concept of CP representing the upper boundary of sustainable exercise, overestimations may be made as the models possess inherent limitations and the protocol design is not always appropriate. Objectives: To measure and compare CP and W’ through the exponential (CPexp), 3-parameter hyperbolic (CP3-hyp), 2-parameter hyperbolic (CP2-hyp), linear (CPlinear), and linear 1/time (CP1/time) models, using different combinations of TTE trials of different durations (approximately 1 to 20 min). Design: Repeated measures. Methods: Thirteen healthy young cyclists (26 ± 3yrs; 69.0 ± 9.2 kg; 174 ± 10 cm; 60.4 ± 5.9mL kg−1 min−1) performed five TTE trials on separate days. CP and W’ were modeled using two, three, four, and/or five trials. All models were compared against a criterion method (CP3-hyp with five trials; confirmed using the leaving-one-out cross-validation analysis) using smallest worthwhile change (SWC) and concordance correlation coefficient (CCC) analyses. Results: CP was considerably overestimated when only trials lasting less than 10 min were included, independent of the mathematical model used. Following CCC analysis, a number of alternative methods were able to predict our criterion method with almost a perfect agreement. However, the application of other common approaches resulted in an overestimation of CP and underestimation of W’, typically these methods only included TTE trials lasting less than 12 min. Conclusions: Estimations from CP3-hyp were found to be the most accurate, independently of TTE range. Models that include two trials between 12 and 20 min provide good agreement with the criterion method (for both CP and W’).
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Purpose: To validate the new drive indoor trainer Hammer designed by Cycleops®. Methods: Eleven cyclists performed 44 randomized and counterbalanced graded exercise tests (100-500W), at 70, 85 and 100 rev.min-1 cadences, in seated and standing positions, on 3 different Hammer units, while a scientific SRM system continuously recorded cadence and power output data. Results: No significant differences were detected between the three Hammer devices and the SRM for any workload, cadence, or pedalling condition (P value between 1.00 and 0.350), except for some minor differences (P 0.03 and 0.04) found in the Hammer 1 at low workloads, and for Hammer 2 and 3 at high workloads, all in seated position. Strong ICCs were found between the power output values recorded by the Hammers and the SRM (≥0.996; P=0.001), independently from the cadence condition and seated position. Bland-Altman analysis revealed low Bias (-5.5-3.8) and low SD of Bias (2.5-5.3) for all testing conditions, except marginal values found for the Hammer 1 at high cadences and seated position (9.6±6.6). High absolute reliability values were detected for the 3 Hammers (150-500W; CV<1.2%; SEM<2.1). Conclusions: This new Cycleops trainer is a valid and reliable device to drive and measure power output in cyclists, providing an alternative to larger and more expensive laboratory ergometers, and allowing cyclists to use their own bicycle.
Article
Lactate or gas exchange threshold (GET) and critical power (CP) are closely associated with human exercise performance. We tested the hypothesis that the limit of tolerance (Tlim) during cycle exercise performed within the exercise intensity domains demarcated by GET and CP is linked to discrete muscle metabolic and neuromuscular responses. Eleven men performed a ramp incremental exercise test, 4–5 severe-intensity (SEV; >CP) constant-work-rate (CWR) tests until Tlim, a heavy-intensity (HVY; GET) CWR test until Tlim, and a moderate-intensity (MOD; <GET) CWR test until Tlim. Muscle biopsies revealed that a similar (P > 0.05) muscle metabolic milieu (i.e., low pH and [PCr] and high [lactate]) was attained at Tlim (approximately 2–14 min) for all SEV exercise bouts. The muscle metabolic perturbation was greater at Tlim following SEV compared with HVY, and also following SEV and HVY compared with MOD (all P < 0.05). The normalized M-wave amplitude for the vastus lateralis (VL) muscle decreased to a similar extent following SEV (−38 ± 15%), HVY (−68 ± 24%), and MOD (−53 ± 29%), (P > 0.05). Neural drive to the VL increased during SEV (4 ± 4%; P < 0.05) but did not change during HVY or MOD (P > 0.05). During SEV and HVY, but not MOD, the rates of change in M-wave amplitude and neural drive were correlated with changes in muscle metabolic ([PCr], [lactate]) and blood ionic/acid-base status ([lactate], [K⁺]) (P < 0.05). The results of this study indicate that the metabolic and neuromuscular determinants of fatigue development differ according to the intensity domain in which the exercise is performed. NEW & NOTEWORTHY The gas exchange threshold and the critical power demarcate discrete exercise intensity domains. For the first time, we show that the limit of tolerance during whole-body exercise within these domains is characterized by distinct metabolic and neuromuscular responses. Fatigue development during exercise greater than critical power is associated with the attainment of consistent “limiting” values of muscle metabolites, whereas substrate availability and limitations to muscle activation may constrain performance at lower intensities.
Article
Purpose: The maximal lactate steady-state (MLSS) is frequently assessed for prescribing endurance exercise intensity. Knowledge of the intra-individual variability of the MLSS is important for practical application. To date, little is known about the reliability of time-to-exhaustion and physiological responses to exercise at MLSS. Methods: Twenty-one healthy men (age, 25.2 (SD 3.3) y; height, 1.83 (0.06) m; body mass, 78.9 (8.9) kg; maximal oxygen uptake, 57.1 (10.7) mL*min-1*kg-1) performed one incremental exercise test, and two constant-load tests to determine MLSS intensity. Subsequently, two open-end constant-load tests (MLSS 1 and 2) at MLSS intensity (3.0 (0.7) W*kg-1, 76% (10%) VO2max) were carried out. During the tests, blood lactate concentrations, heart rate, ratings of perceived exertion (RPE), variables of gas exchange and core body temperature were determined. Results: Time-to-exhaustion was 50.8 (14.0) and 48.2 (16.7) min in MLSS 1 and 2 (mean change -2.6 (95% confidence interval -7.8, 2.6)), respectively. The coefficient of variation (CV) was high for time-to-exhaustion (24.6%) and for mean (4.8 (1.2) mmol*L-1) and end (5.4 (1.7) mmol*L-1) blood lactate concentrations (15.7% and 19.3%). The CV of mean exercise values for all other parameters ranged from 1.4% (core temperature) to 8.3% (ventilation). At termination, the CVs ranged from 0.8% (RPE) to 11.8% (breathing frequency). Conclusion: The low reliability of time-to-exhaustion and blood lactate concentration at MLSS indicates that the precise individual intensity prescription may be challenging. Moreover, the obtained data may serve as reference to allow for the separation of intervention effects from random variation in our sample.
Article
We determined if dehydration alone or in combination with hyperthermia accelerates muscle glycogen use during intense exercise. Seven endurance-trained cyclists (VO2max = 54.4 ± 1.05 mL/kg/min) dehydrated 4.6% of body mass (BM) during exercise in the heat (150 min at 33 ± 1 °C, 25 ± 2% humidity). During recovery (4 h), subjects remained dehydrated (HYPO trial) or recovered all fluid losses (REH trials). Finally, subjects exercised intensely (75% VO2max ) for 40 min in a neutral (25 ± 1 °C; HYPO and REH trials) or in a hot environment (36 ± 1 °C; REHHOT ). Before the final exercise bout vastus lateralis glycogen concentration was similar in all three trials (434 ± 57 mmol/kg of dry muscle (dm)) but muscle water content was lower in the HYPO (357 ± 14 mL/100 g dm) than in REH trials (389 ± 25 and 386 ± 25 mL/100 g dm; P < 0.05). After 40 min of intense exercise, intestinal temperature was similar between the HYPO and REHHOT trials (39.2 ± 0.5 and 39.2 ± 0.4 °C, respectively) and glycogen use was similar (172 ± 86 and 185 ± 97 mmol/kg dm, respectively) despite large differences in muscle water content. In contrast, during REH, intestinal temperature (38.5 ± 0.4 °C) and glycogen use (117 ± 52 mmol/kg dm) were significantly lower than during HYPO and REHHOT . Our data suggest that hyperthermia stimulates glycogen use during intense exercise while muscle water deficit has a minor role. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Article
Bergstrom, HC, Housh, TJ, Zuniga, JM, Traylor, DA, Lewis, RW Jr, Camic, CL, Schmidt, RJ, and Johnson, GO. Differences among estimates of critical power and anaerobic work capacity derived from five mathematical models and the three-minute all-out test. J Strength Cond Res 28(3): 592-600, 2014-Estimates of critical power (CP) and anaerobic work capacity (AWC) from the power output vs. time relationship have been derived from various mathematical models. The purpose of this study was to examine estimates of CP and AWC from the multiple work bout, 2- and 3-parameter models, and those from the 3-minute all-out CP (CP3min) test. Nine college-aged subjects performed a maximal incremental test to determine the peak oxygen consumption rate and the gas exchange threshold. On separate days, each subject completed 4 randomly ordered constant power output rides to exhaustion to estimate CP and AWC from 5 regression models (2 linear, 2 nonlinear, and 1 exponential). During the final visit, CP and AWC were estimated from the CP3min test. The nonlinear 3-parameter (Nonlinear-3) model produced the lowest estimate of CP. The exponential (EXP) model and the CP3min test were not statistically different and produced the highest estimates of CP. Critical power estimated from the Nonlinear-3 model was 14% less than those from the EXP model and the CP3min test and 4-6% less than those from the linear models. Furthermore, the Nonlinear-3 and nonlinear 2-parameter (Nonlinear-2) models produced significantly greater estimates of AWC than did the linear models and CP3min. The current findings suggested that the Nonlinear-3 model may provide estimates of CP and AWC that more accurately reflect the asymptote of the power output vs. time relationship, the demarcation of the heavy and severe exercise intensity domains, and anaerobic capabilities than will the linear models and CP3min test.
Article
The basis of the critical power concept is that there is a hyperbolic relationship between power output and the time that the power output can be sustained. The relationship can be described based on the results of a series of 3 to 7 or more timed all-out predicting trials. Theoretically, the power asymptote of the relationship, CP (critical power), can be sustained without fatigue; in fact, exhaustion occurs after about 30 to 60 minutes of exercise at CP. Nevertheless, CP is related to the fatigue threshold, the ventilatory and lactate thresholds, and maximum oxygen uptake (V̇O2max), and it provides a measure of aerobic fitness. The second parameter of the relationship, AWC (anaerobic work capacity), is related to work performed in a 30-second Wingate test, work in intermittent high-intensity exercise, and oxygen deficit, and it provides a measure of anaerobic capacity. The accuracy of the parameter estimates may be enhanced by careful selection of the power outputs for the predicting trials and by performing a greater number of trials. These parameters provide fitness measures which are mode-specific, combine energy production and mechanical efficiency in 1 variable, and do not require the use of expensive equipment or invasive procedures. However, the attractiveness of the critical power concept diminishes if too many predicting trials are required for generation of parameter estimates with a reasonable degree of accuracy.
Article
Exercise prescribed according to relative intensity is a routine feature in the exercise science literature and is intended to produce an approximately equivalent exercise stress in individuals with different absolute exercise capacities. The traditional approach has been to prescribe exercise intensity as a percentage of maximal oxygen uptake (VO2max) or maximum heart rate (HRmax) and these methods remain common in the literature. However, exercise intensity prescribed at a %VO2max or %HRmax does not necessarily place individuals at an equivalent intensity above resting levels. Furthermore, some individuals may be above and others below metabolic thresholds such as the aerobic threshold (AerT) or anaerobic threshold (AnT) at the same %VO2max or %HRmax. For these reasons, some authors have recommended that exercise intensity be prescribed relative to oxygen consumption reserve (VO2R), heart rate reserve (HRR), the AerT, or the AnT rather than relative to VO2max or HRmax. The aim of this review was to compare the physiological and practical implications of using each of these methods of relative exercise intensity prescription for research trials or training sessions. It is well established that an exercise bout at a fixed %VO2max or %HRmax may produce interindividual variation in blood lactate accumulation and a similar effect has been shown when relating exercise intensity to VO2R or HRR. Although individual variation in other markers of metabolic stress have seldom been reported, it is assumed that these responses would be similarly heterogeneous at a %VO2max, %HRmax, %VO2R, or %HRR of moderate-to-high intensity. In contrast, exercise prescribed relative to the AerT or AnT would be expected to produce less individual variation in metabolic responses and less individual variation in time to exhaustion at a constant exercise intensity. Furthermore, it would be expected that training prescribed relative to the AerT or AnT would provide a more homogenous training stimulus than training prescribed as a %VO2max. However, many of these theoretical advantages of threshold-related exercise prescription have yet to be directly demonstrated. On a practical level, the use of threshold-related exercise prescription has distinct disadvantages compared to the use of %VO2max or %HRmax. Thresholds determined from single incremental tests cannot be assumed to be accurate in all individuals without verification trials. Verification trials would involve two or three additional laboratory visits and would add considerably to the testing burden on both the participant and researcher. Threshold determination and verification would also involve blood lactate sampling, which is aversive to some participants and has a number of intrinsic and extrinsic sources of variation. Threshold measurements also tend to show higher day-to-day variation than VO2max or HRmax. In summary, each method of prescribing relative exercise intensity has both advantages and disadvantages when both theoretical and practical considerations are taken into account. It follows that the most appropriate method of relative exercise intensity prescription may vary with factors such as exercise intensity, number of participants, and participant characteristics. Considering a method's limitations as well as advantages and increased reporting of individual exercise responses will facilitate accurate interpretation of findings and help to identify areas for further study.
Article
A new conception of dynamic or static muscular work tests is presented. The authors define the critical power of a muscular work from the notions of maximum work and maximum time of work. The work capacity is then considered in the case of dynamic work, and of continuous or intermittent static work. From the data presented it is possible to define the maximum amount of work that can be performed in a given time as well as the conditions of work performed without fatigue. (French & German summaries) (22 ref.) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Article
This study was designed to determine whether V˙O(2) reaches a maximum, equivalent to that attained in an incremental exercise test to exhaustion, during "submaximal" fatigue-inducing constant-power exercise bouts above critical power (CP). Nine males (age = 24.6 ± 3.6 yr, height = 182.8 ± 6.9 cm, weight = 77.8 ± 12.1 kg) and four females (age = 29.0 ± 7.3 yr, height = 170.8 ± 3.2 cm, weight = 61.8 ± 8.2 kg) underwent an incremental V˙O(2max) test (IET) on a cycle ergometer, followed by four or five randomly assigned constant-power exercise bouts to exhaustion, on separate days. The CP for each subject was estimated using linear and nonlinear regression. IET V˙O(2max) averaged 3.55 ± 0.92 L·min (RER = 1.21 ± 0.05, HR = 186 ± 10 bpm, 96.1% ± 6.3% of age-predicted maximum). Mean peak V˙O(2) (range = 3.32 ± 0.88 to 3.54 ± 0.91 L·min) during the three highest constant-power bouts (two of which were 53 to 82 W less than peak power output attained during IET) was not significantly different from IET V˙O(2max). Eleven of 13 subjects exceeded their IET V˙O(2max) during at least one of the constant-power exercise bouts. However, peak V˙O(2) (3.11 ± 0.79 L·min) during the lowest constant-power exercise bout, which ranged from 10 to 36 W above CP estimated with a two-parameter nonlinear model, was significantly lower than IET V˙O(2max) (88.2% ± 9.4% of IET V˙O(2max)). At power outputs above CP, V˙O(2) does not necessarily increase to maximum during constant-power exercise to exhaustion. In addition, the highest V˙O(2) values measured during a traditional V˙O(2) "max" test (i.e., IET) may not reflect the highest attainable V˙O(2) despite V˙O(2max) criteria being met.
Article
The critical power (CP) is mathematically defined as the power-asymptote of the hyperbolic relationship between power output and time-to-exhaustion. Physiologically, the CP represents the boundary between the steady-state and nonsteady state exercise intensity domains and therefore may provide a more meaningful index of performance than other well-known landmarks of aerobic fitness such as the lactate threshold and the maximal O2 uptake. Despite the potential importance to sports performance, the CP is often misinterpreted as a purely mathematical construct which lacks physiological meaning and only in recent years has this concept begun to emerge as valid and useful technique for monitoring endurance fitness. This commentary defines the basic principles of the CP concept, outlines its importance to high-intensity exercise performance, and provides an overview of the current methods available for its assessment. Interventions including training, pacing and prior exercise can be used to alter the parameters of the power-time relationship. A future challenge lies in optimizing such interventions in order to positively affect the parameters of the power-time relationship and thereby enhance sports performance in specific events.
Article
In this study we evaluated the physiological and biomechanical responses of 'elite-national class' (i.e., group 1; N = 9) and 'good-state class' (i.e., group 2; N = 6) cyclists while they simulated a 40 km time-trial in the laboratory by cycling on an ergometer for 1 h at their highest power output. Actual road racing 40 km time-trial performance was highly correlated with average absolute power during the 1 h laboratory performance test (r = -0.88; P < 0.001). In turn, 1 h power output was related to each cyclists' V̇O2 at the blood lactate threshold (r = 0.93; P < 0.001). Group 1 was not different from group 2 regarding V̇O(2max) (approximately 70 ml·kg-1·min-1 and 5.01 l·min-1) or lean body weight. However, group 1 bicycled 40 km on the road 10% faster than group 2 (P < 0.05; 54 vs 60 min). Additionally, group 1 was able to generate 11% more power during the 1 h performance test than group 2 (P < 0.05), and they averaged 90 ± 1% V̇O(2max) compared with 86 ± 2% V̇O(2max) in group 2 (P = 0.06). The higher performance power output of group 1 was produced primarily by generating higher peak torques about the center of the crank by applying larger vertical forces to the crank arm during the cycling downstroke. Compared with group 2, group 1 also produced higher peak torques and vertical forces during the downstroke even when cycling at the same absolute work rate as group 2. Factors possibly contributing to the ability of group 1 to produce higher 'downstroke power' are a greater percentage of Type I muscle fibers (P < 0.05) and a 23% greater (P < 0.05) muscle capillary density compared with group 2. We have also observed a strong relationship between years of endurance training and percent Type I muscle fibers (r = 0.75; P < 0.001). It appears that 'elite-national class' cyclists have the ability to generate higher 'downstroke power', possibly as a result of muscular adaptations stimulated by more years of endurance training.
Article
The purpose of this study was to determine the relationship between actual time to exhaustion or time limit (ATLIM) during bicycle ergometry and predicted time to exhaustion (PTLIM) from the Critical Power (CP) test. fourteen males (means +/- SD = 22.36 +/- 2.13 years) volunteered as subjects for this investigation. The subjects visited the laboratory on seven occasions separated by at least 24 h. The first two visits were used for the determination of CP; during the remaining sessions the subjects rode a Monarch bicycle ergometer at power loadings of CP - 20%, CP, CP + 20%, CP + 40% and CP + 60% for the determination of ATLIM. Theoretically, power loadings less than or equal to CP can be maintained indefinitely without exhaustion and the PTLIM for power loadings greater than CP can be estimated from the results of the CP test. The accuracy of the CP test for estimating the time to exhaustion during bicycle ergometry was determined by comparing ATLIM to PTLIM using correlation coefficients, standard error of estimates and related t-tests. The results of this study indicated that there were no significant (p greater than 0.05) differences between ATLIM and PTLIM for power loadings greater than CP (ATLIM vs PTLIM at CP + 20% = 8.19 +/- 3.90 vs 7.13 +/- 2.69 min, t = 2.106, r = 0.893, SEE = 1.21 min; CP + 40% = 3.60 +/- 1.37 vs 3.46 +/- 1.18 min, t = 0.842, r = 0.882, SEE = 0.556 min; CP + 60% = 2.36 +/- 0.95 vs 2.32 +/- 0.79 min; t = 0.328 r = 0.841, SEE = 0.428 min).(ABSTRACT TRUNCATED AT 250 WORDS)
Article
Interest in tests of short-term maximal exercise capacity has increased during recent years. The purpose of this investigation was therefore to study how heart rates and ratings of perceived exertion increase during a work test when the subjects only have to exercise at each work load for 0.5 min and to study predictability of maximal performances. A differential test is obtained by using a series of submaximal ratings to estimate the exercise intensity that can be maintained for only 30 s. The validity of the estimated intensity was checked by having the subject exercise at that load. The test time obtained was then used to correct the estimated exercise intensity according to the general function describing the relation between exercise intensity and exercise time for maximal performances. In the validation the test performances were compared to results from (a) common submaximal ergometer test, and (b) a special test measuring dynamic muscular strength.
Article
The purpose of this study was to evaluate the effect of pedal cadence methodology on the relationship between power output and time to exhaustion. Twenty-four subjects each performed 12 all-out cycle ergometer tests (four at a constant 60 rpm, four at a constant 100 rpm, and four where they were allowed to select and, within each test, vary their cadence). The parameters of the hyperbolic power-time relationship, AWC (anaerobic work capacity) and CP (critical power), were estimated for each pedal cadence methodology using three regression models: nonlinear power-time, linear work-time, and linear power-time-1. In all cases, R2 was high and standard errors of the estimate of AWC and CP were low. With the two constant rpm methodologies, the estimates of AWC and CP were influenced by the choice of regression model. The estimates of AWC and CP were also influenced by the pedal cadence in the all-out tests. For example, the CP derived from the 100 rpm tests (mean +/- SD: 195 +/- 50 W) was lower (p < 0.05) than the CP from the other methodologies (207 +/- 50 W and 204 +/- 48 W), and the AWC from the variable cadence methodology (16.1 +/- 6.2 kJ) was greater than the AWC from constant rpm trials (14.5 +/- 5.9 kJ and 14.6 +/- 5.7 kJ). It is concluded that pedal cadence methodology influences the parameters of the power-time relationship.
Article
Sixteen young, healthy males each performed five to seven randomly assigned, exhaustive exercise bouts on a cycle ergometer, with each bout on a separate day and at a different power, to compare estimates of critical power (PC) and anaerobic work capacity (W') among five different models: t = W'/(Pmax-PC) (two-parameter nonlinear); t = (W'/P-PC))-(W'/(Pmax-PC)) (three-parameter nonlinear); P.t = W' + (PC.t) (linear (P.t)); P = (W'/t) + PC (linear (P)); P = PC + (Pmax-PC)exp(-t/tau) (exponential). The data fit each of the models well (mean R2 = 0.96 through 1.00 for each model). However, significant differences among models were observed for both PC (mean +/- standard deviation (SD) for each model was 195 +/- 29 W through 242 +/- 21 W) and W' (18 +/- 5 kJ through 58 +/- 19 kJ). PC estimates among models were significantly correlated (r = 0.78 through 0.99). For W', between-model correlations ranged from 0.25 to 0.95. For a group of six subjects, the ventilatory threshold for long-term exercise (LTE Tvent; 189 +/- 34 W) was significantly lower than PC for all models except the three-parameter nonlinear (PC = 197 +/- 30 W); PC for each model was, however, positively correlated with LTE Tvent (r = 0.69 through 0.91).(ABSTRACT TRUNCATED AT 250 WORDS)
Article
This study was designed to evaluate the stability of target heart rate (HR) values corresponding to performance markers such as lactate threshold (LT) and the first and second ventilatory thresholds (VT1, VT2) in a group of 13 professional road cyclists (VO2max, approximately 75.0 mL x kg(-1) x min(-1)) during the course of a complete sports season. Each subject performed a progressive exercise test on a bicycle ergometer (ramp protocol with workload increases of 25 W x min(-1)) three times during the season corresponding to the "active" rest (fall: November), precompetition (winter: January), and competition periods (spring: May) to determine HR values at LT, VT1 and VT2. Despite a significant improvement in performance throughout the training season (i.e., increases in the power output eliciting LT, VT1, or VT2), target HR values were overall stable (HR at LT: 154 +/- 3, 152 +/- 3, and 154 +/- 2 beats x min(-1); HR at VT1: 155 +/- 3, 156 +/- 3, and 159 +/- 3 beats x min(-1); and at VT2: 178 +/- 2, 173 +/- 3, and 176 +/- 2 beats x min(-1) during rest, precompetition, and competition periods, respectively). A single laboratory testing session at the beginning of the season might be sufficient to adequately prescribe training loads based on HR data in elite endurance athletes such as professional cyclists. This would simplify the testing schedule generally used for this type of athlete.
Article
We hypothesised that: (1) the maximal lactate steady state (MLSS), critical power (CP) and electromyographic fatigue threshold (EMG(FT)) occur at the same power output in cycling exercise, and (2) exercise above the power output at MLSS (P-MLSS) results in continued increases in oxygen uptake (VO(2)), blood lactate concentration ([La]) and integrated electromyogram (iEMG) with time. Eight healthy subjects [mean (SD) age 25 (3) years, body mass 72.1 (8.2) kg] performed a series of laboratory tests for the determination of MLSS, CP and EMG(FT). The CP was determined from four exhaustive trials of between 2 and 15 min duration. The MLSS was determined as the highest power output at which the increase in blood [La] was less than 1.0 mM across the last 20 min of a series of 30-min trials. The EMG(FT) was determined from four trials of 2 min duration at different power outputs. The surface electromyogram was recorded continuously from the vastus lateralis muscle. The CP was significantly higher than the P-MLSS [242 (25) vs. 222 (23) W; P<0.05], although the two variables were strongly correlated (r=0.95; P<0.01). The EMG(FT) could not be determined in 50% of the subjects. Blood [La], VO(2) and minute ventilation all increased significantly with time for exercise at power outputs above the P-MLSS. In conclusion, the P-MLSS, and not the CP, represents the upper limit of the heavy exercise domain in cycling. During exercise above the P-MLSS, there is no association between changes in iEMG and increases in VO(2) and blood [La] with time.