Validity and reliability of critical power field testing.

PURPOSE: To test the validity and reliability of field critical power (CP). METHOD: Laboratory CP tests comprised three exhaustive trials at intensities of 80, 100 and 105 % maximal aerobic power and CP results were compared with those determined from the field. Experiment 1: cyclists performed three CP field tests which comprised maximal efforts of 12, 7 and 3 min with a 30 min recovery between efforts. Experiment 2: cyclists performed 3 × 3, 3 × 7 and 3 × 12 min individual maximal efforts in a randomised order in the field. Experiment 3: the highest 3, 7 and 12 min power outputs were extracted from field training and racing data. RESULTS: Standard error of the estimate of CP was 4.5, 5.8 and 5.2 % for experiments 1-3, respectively. Limits of agreement for CP were -26 to 29, 26 to 53 and -34 to 44 W for experiments 1-3, respectively. Mean coefficient of variation in field CP was 2.4, 6.5 and 3.5 % for experiments 1-3, respectively. Intraclass correlation coefficients of the three repeated trials for CP were 0.99, 0.96 and 0.99 for experiments 1-3, respectively. CONCLUSIONS: Results suggest field-testing using the different protocols from this research study, produce both valid and reliable CP values.

High agreement between laboratory and field estimates of critical power in cycling.

The purpose of this study was to investigate the level of agreement between laboratory-based estimates of critical power (CP) and results taken from a novel field test. Subjects were fourteen trained cyclists (age 40±7 yrs; body mass 70.2±6.5 kg; VO2max 3.8±0.5 L · min-1). Laboratory-based CP was estimated from 3 constant work-rate tests at 80%, 100% and 105% of maximal aerobic power (MAP). Field-based CP was estimated from 3 all-out tests performed on an outdoor velodrome over fixed durations of 3, 7 and 12 min. Using the linear work limit (Wlim) vs. time limit (Tlim) relation for the estimation of CP1 values and the inverse time (1/t) vs. power (P) models for the estimation of CP2 values, field-based CP1 and CP2 values did not significantly differ from laboratory-based values (234±24.4 W vs. 234±25.5 W (CP1); P<0.001; limits of agreement [LOA], -10.98-10.8 W and 236±29.1 W vs. 235±24.1 W (CP2); P<0.001; [LOA], -13.88-17.3 W. Mean prediction errors for laboratory and field estimates were 2.2% (CP) and 27% (W'). Data suggest that employing all-out field tests lasting 3, 7 and 12 min has potential utility in the estimation of CP.

The 3-min test does not provide a valid measure of critical power using the SRM isokinetic mode.

Recent datas suggest that the mean power over the final 30 s of a 3-min all-out test is equivalent to Critical Power (CP) using the linear ergometer mode. The purpose of the present study was to identify whether this is also true using an "isokinetic mode". 13 cyclists performed: 1) a ramp test; 2) three 3-min all-out trials to establish End Power (EP) and work done above EP (WEP); and 3) 3 constant work rate trials to determine CP and the work done above CP (W') using the work-time (=CP1/W'1) and 1/time (=CP2/W'2) models. Coefficient of variation in EP was 4.45% between trials 1 and 2, and 4.29% between trials 2 and 3. Limits of Agreement for trials 1-2 and trials 2-3 were -2±38 W. Significant differences were observed between EP and CP1 (+37 W, P<0.001), between WEP and W'1(-6.2 kJ, P=0.001), between EP and CP2 (+31 W, P<0.001) and between WEP and W'2 (-4.2 kJ, P=0.006). Average SEE values for EP-CP1 and EP-CP2 of 7.1% and 6.6% respectively were identified. Data suggest that using an isokinetic mode 3-min all-out test, while yielding a reliable measure of EP, does not provide a valid measure of CP.

The effect of turbo trainer cycling on pedalling technique and cycling efficiency.

Cycling can be performed on the road or indoors on stationary ergometers. The purpose of this study was to investigate differences in cycling efficiency, muscle activity and pedal forces during cycling on a stationary turbo trainer compared with a treadmill. 19 male cyclists cycled on a stationary turbo trainer and on a treadmill at 150, 200 and 250 W. Cycling efficiency was determined using the Douglas bags, muscle activity patterns were determined using surface electromyography and pedal forces were recorded with instrumented pedals. Treadmill cycling induced a larger muscular contribution from Gastrocnemius Lateralis, Biceps Femoris and Gluteus Maximus of respectively 14%, 19% and 10% compared with turbo trainer cycling (p<0.05). Conversely, Turbo trainer cycling induced larger muscular contribution from Vastus Lateralis, Rectus Femoris and Tibialis Anterior of respectively 7%, 17% and 14% compared with treadmill cycling (p<0.05). The alterations in muscle activity resulted in a better distribution of power during the pedal revolution, as determined by an increased Dead Centre size (p<0.05). Despite the alterations in muscle activity and pedalling technique, no difference in efficiency between treadmill (18.8±0.7%) and turbo trainer (18.5±0.6%) cycling was observed. These results suggest that cycling technique and type of ergometer can be altered without affecting cycling efficiency.

Inverse relationship between V˙O2max and gross efficiency.

The aim of this study was to identify if an inverse relationship exists between Gross Efficiency (GE) and V˙O2max in trained cyclists. In Experiment 1, 14 trained cyclist's GE and V˙O2max were recorded at 5 different phases of a cycling 'self-coached' season using an incremental laboratory test. In Experiment 2, 29 trained cyclists undertook 12 weeks of training in one of 2 randomly allocated groups (A and B). Over the first 6 weeks Group A was prescribed specific high-intensity training sessions, whilst Group B were restricted in the amount of intensive work they could conduct. In the second 6-week period, both groups were allowed to conduct high intensity training. Results of both experiments in this study demonstrate training related increases in GE, but not V˙O2max. A significant inverse within-subject correlation was evident in experiment 1 between GE and V˙O2max across the training season (r=-0.32; P<0.05). In experiment 2, a significant inverse within-subject correlation was found between changes in GE and V˙O2max in Group A over the first 6 weeks of training (r=-0.78; P<0.01). Resultantly, a training related inverse relationship between GE and V˙O2max is evident in these groups of trained cyclists.

Controversies in the physiological basis of the 'anaerobic threshold' and their implications for clinical cardiopulmonary exercise testing.

This article reviews the notion of the 'anaerobic threshold' in the context of cardiopulmonary exercise testing. Primarily, this is a review of the proposed mechanisms underlying the ventilatory and lactate response to incremental exercise, which is important to the clinical interpretation of an exercise test. Since such tests are often conducted for risk stratification before major surgery, a failure to locate or justify the existence of an anaerobic threshold will have some implications for clinical practice. We also consider alternative endpoints within the exercise response that might be better used to indicate a patient's capacity to cope with the metabolic demands encountered both during and following major surgery.

Validity and reliability of the Wattbike cycle ergometer.

The purpose of this study was to assess the validity and reliability of the Wattbike cycle ergometer against the SRM Powermeter using a dynamic calibration rig (CALRIG) and trained and untrained human participants. Using the CALRIG power outputs of 50-1 250 W were assessed at cadences of 70 and 90 rev x min(-1). Validity and reliability data were also obtained from 3 repeated trials in both trained and untrained populations. 4 work rates were used during each trial ranging from 50-300 W. CALRIG data demonstrated significant differences (P<0.05) between SRM and Wattbike across the work rates at both cadences. Significant differences existed in recorded power outputs from the SRM and Wattbike during steady state trials (power outputs 50-300 W) in both human populations (156±72 W vs. 153±64 W for SRM and Wattbike respectively; P<0.05). The reliability (CV) of the Wattbike in the untrained population was 6.7% (95%CI 4.8-13.2%) compared to 2.2% with the SRM (95%CI 1.5-4.1%). In the trained population the Wattbike CV was 2.6% (95%CI 1.8-5.1%) compared to 1.1% with the SRM (95%CI 0.7-2.0%). These results suggest that when compared to the SRM, the Wattbike has acceptable accuracy. Reliability data suggest coaches and cyclists may need to use some caution when using the Wattbike at low power outputs in a test-retest setting.

Inter- and intra-session reliability of muscle activity patterns during cycling.

The aim of this study was to determine the inter- and intra-session reliability of the temporal and magnitude components of activity in eight muscles considered important for the leg cycling action. On three separate occasions, 13 male non-cyclists and 11 male cyclists completed 6 min of cycling at 135, 150, and 165 W. Cyclists completed two additional 6-min bouts at 215 and 265 W. Surface electromyography was used to record the electrical activity of tibialis anterior, soleus, gastrocnemius medialis, gastrocnemius lateralis, vastus medialis, vastus lateralis, rectus femoris, and gluteus maximus. There were no differences (P > 0.05) in the muscle activity onset and offset or in the iEMG of any muscles between visits. There were also no differences (P > 0.05) between cyclists and non-cyclists in the variability of these parameters. Overall, standard error of measurement (SEM) and intra-class correlation analyses suggested similar reliability of both inter- and intra-session muscle activity onset and offset. The SEM of activity onset in tibialis anterior and activity offset in soleus, gastrocnemius lateralis and rectus femoris was markedly higher than in the other muscles. Intra-session iEMG was reliable (coefficient of variation (CV) = 5.3-13.5%, across all muscles), though a CV range of 15.8-43.1% identified low inter-session iEMG reliability. During submaximal cycling, the temporal components of muscle activity exhibit similar intra- and inter-session reliability. The magnitude component of muscle activity is reliable on an intra-session basis, but not on an inter-session basis.

Allometric scaling of uphill cycling performance.

Previous laboratory-based investigations have identified optimal body mass scaling exponents in the range 0.79-0.91 for uphill cycling. The purpose of this investigation was to evaluate whether or not these exponents are also valid in a field setting. A proportional allometric model was used to predict the optimal power-to-mass ratios associated with road-based uphill time-trial cycling performance. The optimal power function models predicting mean cycle speed during a 5.3 km, 5.4% road hill-climb time-trial were (VO(2max) x m(-1.24))(0.55) and (RMP(max) x m(-1.04))(0.54), explained variance being 84.6% and 70.5%, respectively. Slightly higher mass exponents were observed when the mass predictor was replaced with the combined mass of cyclist and equipment (m(C)). Uphill cycling speed was proportional to (VO(2max) x m(C)(-1.33))(0.57) and (RMP(max) x m(C)(-1.10))(0.59). The curvilinear exponents, 0.54-0.59, identified a relatively strong curvilinear relationship between cycling speed and energy cost, suggesting that air resistance remains influential when cycling up a gradient of 5.4%. These results provide some support for previously reported uphill cycling mass exponents derived in laboratories. However, the exponents reported here were a little higher than those reported previously, a finding possibly explained by a lack of geometric similarity in this sample.

Influence of body position when considering the ecological validity of laboratory time-trial cycling performance.

The aims of this study were to compare the physiological demands of laboratory- and road-based time-trial cycling and to examine the importance of body position during laboratory cycling. Nine male competitive but non-elite cyclists completed two 40.23-km time-trials on an air-braked ergometer (Kingcycle) in the laboratory and one 40.23-km time-trial (RD) on a local road course. One laboratory time-trial was conducted in an aerodynamic position (AP), while the second was conducted in an upright position (UP). Mean performance speed was significantly higher during laboratory trials (UP and AP) compared with the RD trial (P < 0.001). Although there was no difference in power output between the RD and UP trials (P > 0.05), power output was significantly lower during the AP trial than during both the RD (P = 0.013) and UP trials (P = 0.003). Similar correlations were found between AP power output and RD power output (r = 0.85, P = 0.003) and between UP power output and RD power output (r = 0.87, P = 0.003). Despite a significantly lower power output in the laboratory AP condition, these results suggest that body position does not affect the ecological validity of laboratory-based time-trial cycling.

The ecological validity of laboratory cycling: Does body size explain the difference between laboratory- and field-based cycling performance?

Previous researchers have identified significant differences between laboratory and road cycling performances. To establish the ecological validity of laboratory time-trial cycling performances, the causes of such differences should be understood. Hence, the purpose of the present study was to quantify differences between laboratory- and road-based time-trial cycling and to establish to what extent body size [mass (m) and height (h)] may help to explain such differences. Twenty-three male competitive, but non-elite, cyclists completed two 25 mile time-trials, one in the laboratory using an air-braked ergometer (Kingcycle) and the other outdoors on a local road course over relatively flat terrain. Although laboratory speed was a reasonably strong predictor of road speed (R2 = 69.3%), a significant 4% difference (P < 0.001) in cycling speed was identified (laboratory vs. road speed: 40.4 +/- 3.02 vs. 38.7 +/- 3.55 km x h(-1); mean +/- s). When linear regression was used to predict these differences (Diff) in cycling speeds, the following equation was obtained: Diff (km x h(-1)) = 24.9 - 0.0969 x m - 10.7 x h, R2 = 52.1% and the standard deviation of residuals about the fitted regression line = 1.428 (km . h-1). The difference between road and laboratory cycling speeds (km x h(-1)) was found to be minimal for small individuals (mass = 65 kg and height = 1.738 m) but larger riders would appear to benefit from the fixed resistance in the laboratory compared with the progressively increasing drag due to increased body size that would be experienced in the field. This difference was found to be proportional to the cyclists' body surface area that we speculate might be associated with the cyclists' frontal surface area.

Optimal power-to-mass ratios when predicting flat and hill-climbing time-trial cycling.

The purpose of this article was to establish whether previously reported oxygen-to-mass ratios, used to predict flat and hill-climbing cycling performance, extend to similar power-to-mass ratios incorporating other, often quick and convenient measures of power output recorded in the laboratory [maximum aerobic power (W(MAP)), power output at ventilatory threshold (W(VT)) and average power output (W(AVG)) maintained during a 1 h performance test]. A proportional allometric model was used to predict the optimal power-to-mass ratios associated with cycling speeds during flat and hill-climbing cycling. The optimal models predicting flat time-trial cycling speeds were found to be (W(MAP)m(-0.48))(0.54), (W(VT)m(-0.48))(0.46) and (W(AVG)m(-0.34))(0.58) that explained 69.3, 59.1 and 96.3% of the variance in cycling speeds, respectively. Cross-validation results suggest that, in conjunction with body mass, W(MAP) can provide an accurate and independent prediction of time-trial cycling, explaining 94.6% of the variance in cycling speeds with the standard deviation about the regression line, s=0.686 km h(-1). Based on these models, there is evidence to support that previously reported VO2-to-mass ratios associated with flat cycling speed extend to other laboratory-recorded measures of power output (i.e. Wm(-0.32)). However, the power-function exponents (0.54, 0.46 and 0.58) would appear to conflict with the assumption that the cyclists' speeds should be proportional to the cube root (0.33) of power demand/expended, a finding that could be explained by other confounding variables such as bicycle geometry, tractional resistance and/or the presence of a tailwind. The models predicting 6 and 12% hill-climbing cycling speeds were found to be proportional to (W(MAP)m(-0.91))(0.66), revealing a mass exponent, 0.91, that also supports previous research.

Scaling maximal oxygen uptake to predict cycling time-trial performance in the field: a non-linear approach.

The purpose of the present article is to identify the most appropriate method of scaling VO2max for differences in body mass when assessing the energy cost of time-trial cycling. The data from three time-trial cycling studies were analysed (N = 79) using a proportional power-function ANCOVA model. The maximum oxygen uptake-to-mass ratio found to predict cycling speed was VO2max(m)(-0.32) precisely the same as that derived by Swain for sub-maximal cycling speeds (10, 15 and 20 mph). The analysis was also able to confirm a proportional curvilinear association between cycling speed and energy cost, given by (VO2max(m)(-0.32))0.41. The model predicts, for example, that for a male cyclist (72 kg) to increase his average speed from 30 km h(-1) to 35 km h(-1), he would require an increase in VO2max from 2.36 l min(-1) to 3.44 l min(-1), an increase of 1.08 l min(-1). In contrast, for the cyclist to increase his mean speed from 40 km h(-1) to 45 km h(-1), he would require a greater increase in VO2max from 4.77 l min(-1) to 6.36 l min(-1), i.e. an increase of 1.59 l min(-1). The model is also able to accommodate other determinants of time-trial cycling, e.g. the benefit of cycling with a side wind (5% faster) compared with facing a predominately head/tail wind (P<0.05). Future research could explore whether the same scaling approach could be applied to, for example, alternative measures of recording power output to improve the prediction of time-trial cycling performance.