Modeling the expenditure and reconstitution of work capacity above critical power

Wearable heart rate sensing and critical power-based whole-body fatigue monitoring in the field

Whole-body fatigue (WBF) presents a concerning risk to construction workers, which can impact function and ultimately lead to accidents and diminished productivity. This study proposes a new WBF monitoring technique by applying the Critical Power (CP) model, a bioenergetic model, with a wrist-worn heart rate sensor. The authors modified the CP model to calculate WBF from the percentage of heart rate reserve (%HRR) and generated a personalized model via WBF perception surveys. Data were collected for two days from 33 workers at four construction sites. The results showed that the proposed technique can monitor field workers' perceived WBF with a mean absolute error of 12.8% and Spearman correlation coefficient of 0.83. This study, therefore, demonstrates the viability of wearable WBF monitoring on construction sites to support programs aimed at improving workplace safety and productivity.

Characterizing the Exponential Profile of W' Recovery Following Partial Depletion

PURPOSE

The aim of this study was to characterize W' recovery kinetics in response to a partial W' depletion. We hypothesized that W' recovery following a partial depletion would be better described by a biexponential than by a monoexponential model.

METHODS

Nine healthy men performed a ramp incremental exercise test, three to five constant load trials to determine critical power and W', and 10 experimental trials to quantify W' depletion. Each experimental trial consisted of two constant load work bouts (WB1 and WB2) interspersed by a recovery interval. WB1 was designed to evoke a 25% or 75% W' depletion (DEP 25% and DEP 75% ). Subsequently, participants recovered for 30, 60, 120, 300, or 600 s and then performed WB2 to exhaustion to calculate the observed W' recovery (W' OBS ). W' OBS data were fitted using monoexponential and biexponential models, both with a variable and with a fixed model amplitude. Root mean square error and Akaike information criterion (AIC c ) were calculated to evaluate the models' goodness-of-fit.

RESULTS

The biexponential model fits were associated with overall lower root mean square error values (0.4% to 5.0%) when compared with the monoexponential models (2.9% to 8.0%). However, ΔAIC c resulted in negative values (-15.5 and -23.3) for the model fits where the amplitude was kept free, thereby favoring the use of a monoexponential model for both depletion conditions. For the model fits where the amplitude was fixed at 100%, ΔAIC c was negative for DEP 25% (-15.0) but positive for DEP 75% (11.2). W' OBS values were strongly correlated between both depletion conditions ( r = 0.92) and positively associated with V̇O 2peak , critical power, and gas exchange threshold ( r = 0.67 to 0.77).

CONCLUSIONS

The present study results did not provide evidence in favor of a biexponential modeling technique to characterize W' recovery following a partial depletion. Moreover, we demonstrated that fixed time constants were insufficient to model W' recovery across different depletion levels, and that W' recovery was positively associated with aerobic fitness. These findings underline the importance of employing variable and individualized time constants in future predictive W' models.

"Falling Behind," "Letting Go," and Being "Outsprinted" as Distinct Features of Pacing in Distance Running

INTRODUCTION

In distance running, pacing is characterized by changes in speed, leading to runners dropping off the leader's pace until a few remain to contest victory with a final sprint. Pacing behavior has been well studied over the last 30 years, but much remains unknown. It might be related to finishing position, finishing time, and dependent on critical speed (CS), a surrogate of physiologic capacity. We hypothesized a relationship between CS and the distance at which runners "fell behind" and "let go" from the leader or were "outsprinted" as contributors to performance.

METHODS

100-m split times were obtained for athletes in the men's 10,000-m at the 2008 Olympics (N = 35). Split times were individually compared with the winner at the point of "falling behind" (successive split times progressively slower than the winner), "letting go" (large increase in time for distance compared with winner), or "outsprinted" (falling behind despite active acceleration) despite being with the leader with 400 m remaining.

RESULTS

Race times ranged between 26:55 and 29:23 (world record = 26:17). There were 3 groups who fell behind at ∼1000 (n = 11), ∼6000 (n = 16), and ∼9000 m (n = 2); let go at ∼4000 (n = 10), ∼7000 (n = 14), and ∼9500 m (n = 5); or were outkicked (n = 6). There was a moderate correlation between CS and finishing position (r = .82), individual mean pace (r = .79), "fell behind" distance (r = .77), and "let go" distance (r = .79). D' balance was correlated with performance in the last 400 m (r = .87).

CONCLUSIONS

Athletes displayed distinct patterns of falling behind and letting go. CS serves as a moderate predictor of performance and final placing. Final placing during the sprint is related to preservation of D' balance.

Testing the predictive capacity of a muscle fatigue model on electrically stimulated adductor pollicis

PURPOSE

Based on the critical power (Pc or critical force; Fc) concept, a recent mathematical model formalised the proportional link between the decrease in maximal capacities during fatiguing exercises and the amount of impulse accumulated above Fc. This study aimed to provide experimental support to this mathematical model of muscle fatigability in the severe domain through testing (i) the model identifiability using non-exhausting tests and (ii) the model ability to predict time to exhaustion (tlim) and maximal force (Fmax) decrease.

METHODS

The model was tested on eight participants using electrically stimulated adductor pollicis muscle force. The Fmax was recorded every 15 s for all tests, including five constant tests to estimate the initial maximal force (Fi), Fc, and a time constant (τ). The model's parameters were used to compare the predicted and observed tlim values of the incremental ramp test and Fmax(t) of the sine test.

RESULTS

The results showed that the model accurately estimated Fi, Fc, and τ (CI95% = 2.7%Fi and 9.1 s for Fc and τ, respectively; median adjusted r2 = 0.96) and predicted tlim and Fmax with low systematic and random errors (11 ± 20% and - 1.8 ± 7.7%Fi, respectively).

CONCLUSION

This study revealed the potential applications of a novel mathematical formalisation that encompasses previous research on the critical power concept. The results indicated that the model's parameters can be determined from non-exhaustive tests, as long as maximal capacities are regularly assessed. With these parameters, the evolution of maximal capacities (i.e. fatigability) at any point during a known exercise and the time to exhaustion can be accurately predicted.

A dynamic model of the bi-exponential reconstitution and expenditure of W' in trained cyclists

ABSTRACTThe aim of this study was to investigate the effects of different recovery power outputs on the reconstitution of W' and to develop a dynamic bi-exponential model of W' during depletion and reconstitution. Ten trained cyclists (mass 71.7 ± 8.4 kg; V̇O2max 60.0 ± 6.3 ml·kg-1·min-1) completed three incremental ramps (20 W·min-1) to the limit of tolerance on each of six occasions with recovery durations of 30 and 240 s. Recovery power outputs varied between 50 W (LOW); 60% of critical power (CP) (MOD) and 85% of CP (HVY). W' reconstitution was measured following each recovery and fitted to a bi-exponential model. Amplitude and time constant (τ) parameters were then determined via regression analysis accounting for relative intensity and duration to produce a dynamic model of W'. W' reconstitution slowed disproportionately as recovery power output increased (p < 0.001) and increased with recovery duration (p < 0.001). The amplitudes of each recovery component were strongly correlated to W' reconstitution after 240 s at HVY (r = 0.95), whilst τ parameters were found to be related to the fractional difference between recovery power and CP. The predictive capacity of the resultant model was assessed against experimental data with no differences found between predicted and experimental values of W' reconstitution (p > 0.05). The dynamic bi-exponential model of W' accounting for varying recovery intensities closely described W' kinetics in trained cyclists facilitating real-time decisions about pacing and tactics during competition. The model can be customised for individuals from known CP and W' and a single additional test session.HighlightsA dynamic bi-exponential model of W' accounting for both varying power output and duration.Individual customisation of the model can be achieved with a single specific test session.W' reconstitution slows disproportionally with increasing intensity after repeated bouts.

Acute Oxygen Consumption Response to Fast Start High-Intensity Intermittent Exercise

The current investigation compared the acute oxygen consumption (VO2) response of two high-intensity interval exercises (HIIE), fast start (FSHIIE), and steady power (SPHIIE), which matched w prime (W') depletion. Eight cyclists completed an incremental max test and a three-minute all-out test (3MT) to determine maximal oxygen consumption (VO2max), critical power (CP), and W'. HIIE sessions consisted of 3 X 4 min intervals interspersed by 3 min of active recovery, with W' depleted by 60% (W'target) within each working interval. SPHIIE depleted the W'target consistently throughout the 3 min intervals, while FSHIIE depleted the W'target by 50% within the first minute, with the remaining 50% depleted evenly across the remainder of the interval. The paired samples t-test revealed no differences in the percentage of training time spent above 90% of VO2max (PT ≥ 90% VO2max) between SPHIIE and FSHIIE with an average of 25.20% and 26.07%, respectively. Pairwise comparisons indicated a difference between minute 1 peak VO2, minute 2, and minute 3, while no differences were present between minutes 2 and 3. The results suggest that when HIIE formats are matched based on W' expenditure, there are no differences in PT ≥ 90% VO2max or peak VO2 during each interval.

Development and validation of dynamic bioenergetic model for intermittent ergometer cycling

PURPOSE

The aim of this study was to develop and validate a bioenergetic model describing the dynamic behavior of the alactic, lactic, and aerobic metabolic energy supply systems as well as different sources of the total metabolic energy demand.

METHODS

The bioenergetic supply model consisted of terms for the alactic, lactic, and aerobic system metabolic rates while the demand model consisted of terms for the corresponding metabolic rates of principal cycling work, pulmonary ventilation, and accumulated metabolites. The bioenergetic model was formulated as a system of differential equations and model parameters were estimated by a non-linear grey-box approach, utilizing power output and aerobic metabolic rate (MRae) data from fourteen cyclists performing an experimental trial (P2) on a cycle ergometer. Validity was assessed by comparing model simulation and measurements on a similar follow-up experimental trial (P3).

RESULTS

The root mean square error between modelled and measured MRae was 61.9 ± 7.9 W and 79.2 ± 30.5 W for P2 and P3, respectively. The corresponding mean absolute percentage error was 8.6 ± 1.5% and 10.6 ± 3.3% for P2 and P3, respectively.

CONCLUSION

The validation of the model showed excellent overall agreement between measured and modeled MRae during intermittent cycling by well-trained male cyclist. However, the standard deviation was 38.5% of the average root mean square error for P3, indicating not as good reliability.

Critical power, W' and W' reconstitution in women and men

PURPOSE

The aim of this study was to compare critical power (CP) and work capacity W', and W' reconstitution (W'REC) following repeated maximal exercise between women and men.

METHODS

Twelve women ([Formula: see text]O2PEAK: 2.53 ± 0.37 L·min-1) and 12 men ([Formula: see text]O2PEAK: 4.26 ± 0.30 L·min-1) performed a minimum of 3 constant workload tests, to determine CP and W', and 1 maximal exercise repetition test with three work bouts (WB) to failure, to quantify W'REC during 2 recovery periods, i.e., W'REC1 and W'REC2. An independent samples t test was used to compare CP and W' values between women and men, and a repeated-measures ANOVA was used to compare W'REC as fraction of W' expended during the first WB, absolute W'REC, and normalized to lean body mass (LBM).

RESULTS

CP normalized to LBM was not different between women and men, respectively, 3.7 ± 0.5 vs. 4.1 ± 0.4 W·kgLBM-1, while W' normalized to LBM was lower in women 256 ± 29 vs. 305 ± 45 J·kgLBM-1. Fractional W'REC1 was higher in women than in men, respectively, 74.0 ± 12.0% vs. 56.8 ± 9.5%. Women reconstituted less W' than men in absolute terms (8.7 ± 1.2 vs. 10.9 ± 2.0 kJ) during W'REC1, while normalized to LBM no difference was observed between women and men (174 ± 23 vs. 167 ± 31 J·kgLBM-1). W'REC2 was lower than W'REC1 both in women and men.

CONCLUSION

Sex differences in W'REC (absolute women < men; fractional women > men) are eliminated when LBM is accounted for. Prediction models of W'REC might benefit from including LBM as a biological variable in the equation. This study confirms the occurrence of a slowing of W'REC during repeated maximal exercise.

Competitive Cross-Country Skiers Have Longer Time to Exhaustion Than Recreational Cross-Country Skiers During Intermittent Work Intervals Normalized to Their Maximal Aerobic Power

PURPOSE

To investigate differences in time to exhaustion (TTE), O2 uptake (V˙O2), and accumulated O2 deficit (O2def) between competitive and recreational cross-country (XC) skiers during an intermittent-interval protocol standardized for maximal aerobic power (MAP).

METHODS

Twelve competitive (maximal V˙O2 [V˙O2max]=76.5±3.8 mL·kg-1·min-1) and 10 recreational (V˙O2max=63.5±6.3 mL·kg-1·min-1) male XC skiers participated. All tests were performed on a rollerski treadmill in the V2 ski-skating technique. To quantify MAP and maximal accumulated oxygen deficit (MAOD), the skiers performed a steady-state submaximal test followed by a 1000-m time trial. After a 60-minute break, TTE, V˙O2, and accumulated O2def were measured during an intermittent-interval protocol (40-s work and 20-s recovery), which was individually tailored to 120% and 60% of each subject's MAP.

RESULTS

During the 1000-m time trial, the competitive skiers had 21% (95% CI, 12%-30%) shorter finish time and 24% (95% CI, 14%-34%) higher MAP (all P < .01) than the recreational skiers. No difference was observed in relative exercise intensity (average power/MAP; P = .28), MAOD (P = .18), or fractional utilization of V˙O2max. During the intermittent-interval protocol, the competitive skiers had 34% (95% CI, 3%-65%) longer TTE (P = .03) and accumulated 61% (95% CI, 27%-95%) more O2def (P = .001) than the recreational skiers during work phases.

CONCLUSIONS

Competitive XC skiers have longer TTE and accumulate more O2def than recreational XC skiers during an intermittent-interval protocol at similar intensity relative to MAP. This implies that performance in intermittent endurance sports is related to the ability to repeatedly recharge fractions of MAOD.

Invited review: The speed-duration relationship across the animal kingdom

The parameters of the hyperbolic speed-duration relationship (the asymptote critical speed, CS, and the curvature constant, D') provide estimates of the maximal steady state speed (CS) and the distance an animal can run, swim, or fly at speeds above CS before it is forced to slow down or stop (D'). The speed-duration relationship has been directly studied in humans, horses, mice and rats. The technical difficulties with treadmill running in dogs and the relatively short greyhound race durations means that, perhaps surprisingly, it has not been assessed in dogs. The endurance capabilities of lizards, crabs and salamanders has also been measured, and the speed-duration relationship can be calculated from these data. These analyses show that 1) raising environmental temperature from 25 °C to 40 °C in lizards can double the CS with no change in D'; 2) that lungless salamanders have an extremely low critical speed due, most likely, to O₂ diffusion limitations associated with cutaneous respiration; and 3) the painted ghost crab possesses the highest endurance parameter ratio (D'/CS) yet recorded (470 s), allowing it to maintain high speeds for extended periods. Although the speed-duration relationship has not been measured in fish, the sustainable swimming speed has been quantified in a range of species and is conceptually similar to the maximal steady state in humans. The high aerobic power of birds and low metabolic cost of transport during flight permits the extreme feats of endurance observed in bird migrations. However, the parameters of the avian speed-duration relationship have not been quantified.

Effect of varying recovery intensities on power outputs during severe intensity intervals in trained cyclists during the Covid-19 pandemic

Purpose

The study aimed to investigate the effects of different recovery intensities on the power outputs of repeated severe intensity intervals and the implications for W' reconstitution in trained cyclists.

Methods

Eighteen trained cyclists (FTP 258.0 ± 42.7 W; weekly training 8.6 ± 1.7 h∙week-1) familiar with interval training, use of the Zwift® platform throughout the Covid-19 pandemic, and previously established FTP (95% of mean power output from a 20-min test), performed 5 × 3-min severe intensity efforts interspersed with 2-min recoveries. Recovery intensities were: 50 W (LOW), 50% of functional threshold power (MOD), and self-selected power output (SELF).

Results

Whilst power outputs declined as the session progressed, mean power outputs during the severe intervals across the conditions were not different to each other (LOW 300.1 ± 48.1 W; MOD: 296.9 ± 50.4 W; SELF: 298.8 ± 53.3 W) despite the different recovery conditions. Mean power outputs of the self-selected recovery periods were 121.7 ± 26.2 W. However, intensity varied during the self-selected recovery periods, with values in the last 15 s being greater than the first 15 s (p < 0.001) and decreasing throughout the session (128.7 ± 25.4 W to 113.9 ± 29.3 W).

Conclusion

Reducing recovery intensities below 50% of FTP failed to enhance subsequent severe intensity intervals, suggesting that a lower limit for optimal W' reconstitution had been reached. As self-selected recoveries were seen to adapt to maintain the severe intensity power output as the session progressed, adopting such a strategy might be preferential for interval training sessions.

A data-driven approach to the "Everesting" cycling challenge

The "Everesting" challenge is a cycling activity in which a cyclist repeats a hill until accumulating an elevation gain equal to the elevation of Mount Everest in a single ride. The challenge experienced a surge in interest during the COVID-19 pandemic and the cancelation of cycling races around the world that prompted cyclists to pursue alternative, individual activities. The time to complete the Everesting challenge depends on the fitness and talent of the cyclist, but also on the length and gradient of the hill, among other parameters. Hence, preparing an Everesting attempt requires understanding the relationship between the Everesting parameters and the time to complete the challenge. We use web-scraping to compile a database of publicly available Everesting attempts, and we quantify and rank the parameters that determine the time to complete the challenge. We also use unsupervised machine learning algorithms to segment cyclists into distinct groups according to their characteristics and performance. We conclude that the power per unit body mass of the cyclist and the tradeoff between the gradient of the hill and the distance are the most important considerations when attempting the Everesting challenge. As such, elite cyclists best select a hill with gradient > 12%, whereas amateur and recreational cyclists best select a hill with gradient < 10% to minimize the time to complete the Everesting challenge.

Accounting for Dynamic Changes in the Power-Duration Relationship Improves the Accuracy of W' Balance Modeling

PURPOSE

This study aimed 1) to examine the accuracy with which W' reconstitution (W' REC ) is estimated by the W' balance (W' BAL ) models after a 3-min all-out cycling test (3MT), 2) to determine the effects of a 3MT on the power-duration relationship, and 3) to assess whether accounting for changes in the power-duration relationship during exercise improved estimates of W' REC .

METHODS

The power-duration relationship and the actual and estimated W' REC were determined for 12 data sets extracted from our laboratory database where participants had completed two 3MT separated by 1-min recovery (i.e., control [C-3MT] and fatigued [F-3MT]).

RESULTS

Actual W' REC (6.3 ± 1.4 kJ) was significantly overestimated by the W' BAL·ODE (9.8 ± 1.3 kJ; P < 0.001) and the W' BAL·MORTON (16.9 ± 2.6 kJ; P < 0.001) models but was not significantly different to the estimate provided by the W' BAL·INT (7.5 ± 1.5 kJ; P > 0.05) model. End power (EP) was 7% lower in the F-3MT (263 ± 40 W) compared with the C-3MT (282 ± 44 W; P < 0.001), and work done above EP (WEP) was 61% lower in the F-3MT (6.3 ± 1.4 kJ) compared with the C-3MT (16.9 ± 3.2 kJ). The size of the error in the estimated W' REC was correlated with the reduction in WEP for the W' BAL·INT and W' BAL·ODE models (both r > -0.74, P < 0.01) but not the W' BAL·MORTON model ( r = -0.18, P > 0.05). Accounting for the changes in the power-duration relationship improved the accuracy of the W' BAL·ODE and W' BAL·MORTON , but they remained significantly different to actual W' REC .

CONCLUSIONS

These findings demonstrate that the power-duration relationship is altered after a 3MT, and accounting for these changes improves the accuracy of the W' BAL·ODE and the W' BAL·MORTON , but not W' BAL·INT models. These results have important implications for the design and use of mathematical models describing the energetics of exercise performance.

Competition Between Desired Competitive Result, Tolerable Homeostatic Disturbance, and Psychophysiological Interpretation Determines Pacing Strategy

Scientific interest in pacing goes back >100 years. Contemporary interest, both as a feature of athletic competition and as a window into understanding fatigue, goes back >30 years. Pacing represents the pattern of energy use designed to produce a competitive result while managing fatigue of different origins. Pacing has been studied both against the clock and during head-to-head competition. Several models have been used to explain pacing, including the teleoanticipation model, the central governor model, the anticipatory-feedback-rating of perceived exertion model, the concept of a learned template, the affordance concept, the integrative governor theory, and as an explanation for "falling behind." Early studies, mostly using time-trial exercise, focused on the need to manage homeostatic disturbance. More recent studies, based on head-to-head competition, have focused on an improved understanding of how psychophysiology, beyond the gestalt concept of rating of perceived exertion, can be understood as a mediator of pacing and as an explanation for falling behind. More recent approaches to pacing have focused on the elements of decision making during sport and have expanded the role of psychophysiological responses including sensory-discriminatory, affective-motivational, and cognitive-evaluative dimensions. These approaches have expanded the understanding of variations in pacing, particularly during head-to-head competition.

Does creatine supplementation affect recovery speed of impulse above critical torque?

We previously reported that creatine supplementation improved intermittent isometric exercise performance by augmenting the total impulse performed above end-test torque (total IET'). However, our previous analyses did not enable mechanistic assessments. The objective of this study was to determine if creatine supplementation affected the IET' speed of recovery. To achieve this objective, we retrospectively analyzed our data using the IET' balance model to determine the time constant for the recovery of IET' (τIET'). Sixteen men were randomly allocated into creatine (N = 8) or placebo (N = 8) groups. Prior to supplementation, participants performed quadriceps all-out exercise to determine end-test torque (ET) and IET'. Participants then performed quadriceps exercise at ET + 10% until task-failure before supplementation (Baseline), until task-failure after supplementation (Creatine or Placebo), and until the Baseline time after supplementation (Creatine- or Placebo-Isotime). τIET' was faster than Baseline for Creatine (669 ± 98 vs 470 ± 66 s), but not Placebo (792 ± 166 vs 786 ± 161 s). The creatine-induced change in τIET' was inversely correlated with the creatine-induced changes in both the rate of peripheral fatigue development and time to task-failure. τIET' was inversely correlated with total IET' and ET in all conditions, but creatine supplementation shifted this relationship such that τIET' was faster for a given ET. Creatine supplementation, therefore, sped the recovery of IET' during intermittent isometric exercise, which was inversely related to the improvement in exercise performance. These findings support that the improvement in exercise performance after creatine supplementation was, at least in part, specific to effects on the physiological mechanisms that determine the IET' speed of recovery. HIGHLIGHTSSixteen healthy participants were randomly allocated to creatine supplementation or placebo groups.Creatine supplementation accelerated the time constant for the recovery of IET' (τIET').The time constant for the recovery of IET' (τIET') was inversely related to both the rate of peripheral fatigue development and the time to task failure.

Modeling the expenditure and reconstitution of distance above critical speed during two swimming interval training sessions

In swimming, the speed-time relationship provides the critical speed (CS) and the maximum distance that can be performed above CS (D′). During intermittent severe intensity exercise, a complete D′ depletion coincides with task failure, while a sub-CS intensity is required for D′ reconstitution. Therefore, determining the balance D′ remaining at any time during intermittent exercise (D'_BAL) could improve training prescription. This study aimed to 1) test the D'_BAL model for swimming; 2) determine an equation to estimate the time constant of the reconstitution of D' (τD′); and 3) verify if τD′ is constant during two interval training sessions with the same work intensity and duration and recovery intensity, but different recovery duration. Thirteen swimmers determined CS and D′ and performed two high-intensity interval sessions at a constant speed, with repetitions fixed at 50 m. The duration of passive recovery was based on the work/relief ratio of 2:1 (T2:1) and 4:1 (T4:1). There was a high variability between sessions for τD' (coefficient of variation of 306%). When τD′ determined for T2:1 was applied in T4:1 and vice versa, the D'_BAL model was inconsistent to predict the time to exhaustion (coefficient of variation of 29 and 28%). No linear or nonlinear relationships were found between τD′ and CS, possibly due to the high within-subject variability of τD'. These findings suggest that τD′ is not constant during two high-intensity interval sessions with the same recovery intensity. Therefore, the current D'_BAL model was inconsistent to track D′ responses for swimming sessions tested herein.

Critical Power, Work Capacity, and Recovery Characteristics of Team-Pursuit Cyclists

PURPOSE

Leading a 4-km team pursuit (TP) requires high-intensity efforts above critical power (CP) that deplete riders' finite work capacity (W'), whereas riders following in the aerodynamic draft may experience some recovery due to reduced power demands. This study aimed to determine how rider ability and CP and W' measures impact TP performance and the extent to which W' can reconstitute during recovery positions in a TP race.

METHODS

Three TP teams, each consisting of 4 males, completed individual performance tests to determine their CP and W'. Teams were classified based on their performance level as international (INT), national (NAT), or regional (REG). Each team performed a TP on an indoor velodrome (INT: 3:49.9; NAT: 3:56.7; and REG: 4:05.4; min:s). Ergometer-based TP simulations with an open-ended interval to exhaustion were performed to measure individual ability to reconstitute W' at 25 to 100 W below CP.

RESULTS

The INT team possessed higher CP (407 [4] W) than both NAT (381 [13] W) and REG (376 [15] W) (P < .05), whereas W' was similar between teams (INT: 27.2 [2.8] kJ; NAT: 29.3 [2.4] kJ; and REG: 28.8 [1.6] kJ; P > .05). The INT team expended 104% (5%) of their initial W' during the TP and possessed faster rates of recovery than NAT and REG at 25 and 50 W below CP (P < .05).

CONCLUSIONS

The CP and rate of W' reconstitution have a greater impact on TP performance than W' magnitude and can differentiate TP performance level.

Everesting: cycling the elevation of the tallest mountain on Earth

Purpose

With few cycling races on the calendar in 2020 due to COVID-19, Everesting became a popular challenge: you select one hill and cycle up and down it until you reach the accumulated elevation of Mt. Everest (8,848 m or 29,029ft). With an almost infinite number of different hills across the world, the question arises what the optimal hill for Everesting would be. Here, we address the biomechanics and energetics of up- and downhill cycling to determine the characteristics of this optimal hill.

Methods

During uphill cycling, the mechanical power output equals the power necessary to overcome air resistance, rolling resistance, and work against gravity, and for a fast Everesting time, one should maximize this latter term. To determine the optimal section length (i.e., number of repetitions), we applied the critical power concept and assumed that the U-turn associated with an additional repetition comes with a 6 s time penalty.

Results

To use most mechanical power to overcoming gravity, slopes of at least 12% are most suitable, especially since gross efficiency seems only minimally diminished on steeper slopes. Next, we found 24 repetitions to be optimal, yet this number slightly depends on the assumptions made. Finally, we discuss other factors (fueling, altitude, fatigue) not incorporated in the model but also affecting Everesting performances.

Conclusion

For a fast Everesting time, our model suggests to select a hill climb which preferably starts at (or close to) sea level, with a slope of 12–20% and length of 2–3 km.

A three-minute all-out test performed in a remote setting does not provide a valid estimate of the maximum metabolic steady state

PURPOSE

The three-minute all-out test (3MT), when performed on a laboratory ergometer in a linear mode, can be used to estimate the heavy-severe-intensity transition, or maximum metabolic steady state (MMSS), using the end-test power output. As the 3MT only requires accurate measurement of power output and time, it is possible the 3MT could be used in remote settings using personal equipment without supervision for quantification of MMSS.

METHODS

The aim of the present investigation was to determine the reliability and validity of remotely performed 3MTs (3MT_R) for estimation of MMSS. Accordingly, 53 trained cyclists and triathletes were recruited to perform one familiarisation and two experimental 3MT_R trials to determine its reliability. A sub-group (N = 10) was recruited to perform three-to-five 30 min laboratory-based constant-work rate trials following completion of one familiarisation and two experimental 3MT_R trials. Expired gases were collected throughout constant-work rate trials and blood lactate concentration was measured at 10 and 30 min to determine the highest power output at which steady-state [Formula: see text] (MMSS-[Formula: see text]) and blood lactate (MMSS-[La^-]) were achieved.

RESULTS

The 3MT_R end-test power (EP_remote) was reliable (coefficient of variation, 4.5% [95% confidence limits, 3.7, 5.5%]), but overestimated MMSS (EP_remote, 283 ± 51 W; MMSS-[Formula: see text], 241 ± 46 W, P = 0.0003; MMSS-[La^-], 237 ± 47 W, P = 0.0003). This may have been due to failure to deplete the finite work capacity above MMSS during the 3MT_R.

CONCLUSION

These results suggest that the 3MT_R should not be used to estimate MMSS in endurance-trained cyclists.

Can Popular High-Intensity Interval Training (HIIT) Models Lead to Impossible Training Sessions?

High-Intensity Interval Training (HIIT) is a time-efficient training method suggested to improve health and fitness for the clinical population, healthy subjects, and athletes. Many parameters can impact the difficulty of HIIT sessions. This study aims to highlight and explain, through logical deductions, some limitations of the Skiba and Coggan models, widely used to prescribe HIIT sessions in cycling. We simulated 6198 different HIIT training sessions leading to exhaustion, according to the Skiba and Coggan-Modified (modification of the Coggan model with the introduction of an exhaustion criterion) models, for three fictitious athlete profiles (Time-Trialist, All-Rounder, Sprinter). The simulation revealed impossible sessions (i.e., requiring athletes to surpass their maximal power output over the exercise interval duration), characterized by a few short exercise intervals, performed in the severe and extreme intensity domains, alternating with long recovery bouts. The fraction of impossible sessions depends on the athlete profile and ranges between 4.4 and 22.9% for the Skiba model and 0.6 and 3.2% for the Coggan-Modified model. For practitioners using these HIIT models, this study highlights the importance of understanding these models’ inherent limitations and mathematical assumptions to draw adequate conclusions from their use to prescribe HIIT sessions.

Bi-exponential modelling of [Formula: see text] reconstitution kinetics in trained cyclists

PURPOSE

The aim of this study was to investigate the individual [Formula: see text] reconstitution kinetics of trained cyclists following repeated bouts of incremental ramp exercise, and to determine an optimal mathematical model to describe [Formula: see text] reconstitution.

METHODS

Ten trained cyclists (age 41 ± 10 years; mass 73.4 ± 9.9 kg; [Formula: see text] 58.6 ± 7.1 mL kg min^-1) completed three incremental ramps (20 W min^-1) to the limit of tolerance with varying recovery durations (15-360 s) on 5-9 occasions. [Formula: see text] reconstitution was measured following the first and second recovery periods against which mono-exponential and bi-exponential models were compared with adjusted R² and bias-corrected Akaike information criterion (AICc).

RESULTS

A bi-exponential model outperformed the mono-exponential model of [Formula: see text] reconstitution (AICc 30.2 versus 72.2), fitting group mean data well (adjR² = 0.999) for the first recovery when optimised with parameters of fast component (FC) amplitude = 50.67%; slow component (SC) amplitude = 49.33%; time constant (τ)_FC = 21.5 s; τ_SC = 388 s. Following the second recovery, W' reconstitution reduced by 9.1 ± 7.3%, at 180 s and 8.2 ± 9.8% at 240 s resulting in an increase in the modelled τ_SC to 716 s with τ_FC unchanged. Individual bi-exponential models also fit well (adjR² = 0.978 ± 0.017) with large individual parameter variations (FC amplitude 47.7 ± 17.8%; first recovery: (τ)_FC = 22.0 ± 11.8 s; (τ)_SC = 377 ± 100 s; second recovery: (τ)_FC = 16.3.0 ± 6.6 s; (τ)_SC = 549 ± 226 s).

CONCLUSIONS

W' reconstitution kinetics were best described by a bi-exponential model consisting of distinct fast and slow phases. The amplitudes of the FC and SC remained unchanged with repeated bouts, with a slowing of W' reconstitution confined to an increase in the time constant of the slow component.

Interaction of exercise bioenergetics with pacing behavior predicts track distance running performance

The best possible finishing time for a runner competing in distance track events can be estimated from their critical speed (CS) and the finite amount of energy that can be expended above CS (D´). During tactical races with variable pacing, the runner with the "best" combination of CS and D´ and, therefore, the fastest estimated finishing time prior to the race, does not always win. We hypothesized that final race finishing positions depend on the relationships between the pacing strategies used, the athletes' initial CS, and their instantaneous D´ (i.e., D´ balance) as the race unfolds. Using publicly available data from the 2017 International Association of Athletics Federations (IAAF) World Championships men's 5,000-m and 10,000-m races, race speed, CS, and D´ balance were calculated. The correlation between D´ balance and actual finishing positions was nonsignificant using start-line values but improved to R² > 0.90 as both races progressed. The D´ balance with 400 m remaining was strongly associated with both final 400-m split time and proximity to the winner. Athletes who exhausted their D´ were unable to hold pace with the leaders, whereas a high D´ remaining enabled a fast final 400 m and a high finishing position. The D´ balance model was able to accurately predict finishing positions in both a "slow" 5,000-m and a "fast" 10,000-m race. These results indicate that although CS and D´ can characterize an athlete's performance capabilities prior to the start, the pacing strategy that optimizes D´ utilization significantly impacts the final race outcome.NEW & NOTEWORTHY We show that the interaction between exercise bioenergetics and real-time pacing strategy predicts track distance running performance. Critical speed (CS) and the finite energy expended above CS (D´) can characterize an athlete's capabilities prior to the race start, but the pacing strategy that optimizes D´ utilization ultimately impacts whether a runner is in contention to win and whether a runner will have a fast final 400 m. Accordingly, D´ balance predicts final race finishing order.

The W' Balance Model: Mathematical and Methodological Considerations

Since its publication in 2012, the W' balance model has become an important tool in the scientific armamentarium for understanding and predicting human physiology and performance during high-intensity intermittent exercise. Indeed, publications featuring the model are accumulating, and it has been adapted for popular use both in desktop computer software and on wrist-worn devices. Despite the model's intuitive appeal, it has achieved mixed results thus far, in part due to a lack of clarity in its basis and calculation. Purpose: This review examines the theoretical basis, assumptions, calculation methods, and the strengths and limitations of the integral and differential forms of the W' balance model. In particular, the authors emphasize that the formulations are based on distinct assumptions about the depletion and reconstitution of W' during intermittent exercise; understanding the distinctions between the 2 forms will enable practitioners to correctly implement the models and interpret their results. The authors then discuss foundational issues affecting the validity and utility of the model, followed by evaluating potential modifications and suggesting avenues for further research. Conclusions: The W' balance model has served as a valuable conceptual and computational tool. Improved versions may better predict performance and further advance the physiology of high-intensity intermittent exercise.

Validity and Reliability of Hydraulic-Analogy Bioenergetic Models in Sprint Roller Skiing

Purpose: To develop a method for individual parameter estimation of four hydraulic-analogy bioenergetic models and to assess the validity and reliability of these models' prediction of aerobic and anaerobic metabolic utilization during sprint roller-skiing. Methods: Eleven elite cross-country skiers performed two treadmill roller-skiing time trials on a course consisting of three flat sections interspersed by two uphill sections. Aerobic and anaerobic metabolic rate contributions, external power output, and gross efficiency were determined. Two versions each (fixed or free maximal aerobic metabolic rate) of a two-tank hydraulic-analogy bioenergetic model (2TM-fixed and 2TM-free) and a more complex three-tank model (3TM-fixed and 3TM-free) were programmed into MATLAB. The aerobic metabolic rate (MR _ae ) and the accumulated anaerobic energy expenditure (E _an,acc ) from the first time trial (STT1) together with a gray-box model in MATLAB, were used to estimate the bioenergetic model parameters. Validity was assessed by simulation of each bioenergetic model using the estimated parameters from STT1 and the total metabolic rate (MR _tot ) in the second time trial (STT2). Results: The validity and reliability of the parameter estimation method based on STT1 revealed valid and reliable overall results for all the four models vs. measurement data with the 2TM-free model being the most valid. Mean differences in model-vs.-measured MR _ae ranged between -0.005 and 0.016 kW with typical errors between 0.002 and 0.009 kW. Mean differences in E _an,acc at STT termination ranged between -4.3 and 0.5 kJ and typical errors were between 0.6 and 2.1 kJ. The root mean square error (RMSE) for 2TM-free on the instantaneous STT1 data was 0.05 kW for MR _ae and 0.61 kJ for E _an,acc , which was lower than the other three models (all P < 0.05). Compared to the results in STT1, the validity and reliability of each individually adapted bioenergetic model was worse during STT2 with models underpredicting MR _ae and overpredicting E _an,acc vs. measurement data (all P < 0.05). Moreover, the 2TM-free had the lowest RMSEs during STT2. Conclusion: The 2TM-free provided the highest validity and reliability in MR _ae and E _an,acc for both the parameter estimation in STT1 and the model validity and reliability evaluation in the succeeding STT2.

Validating an Adjustment to the Intermittent Critical Power Model for Elite Cyclists-Modeling W' Balance During World Cup Team Pursuit Performances

PURPOSE

Modeling intermittent work capacity is an exciting development to the critical power model with many possible applications across elite sport. With the Skiba 2 model validated using subelite participants, an adjustment to the model's recovery rate has been proposed for use in elite cyclists (Bartram adjustment). The team pursuit provides an intermittent supramaximal event with which to validate the modeling of W' in this population.

METHODS

Team pursuit data of 6 elite cyclists competing for Australia at a Track World Cup were solved for end W' values using both the Skiba 2 model and the Bartram adjustment. Each model's success was evaluated by its ability to approximate end W' values of 0 kJ, as well as a count of races modeled to within a predetermined error threshold of ±1.840 kJ.

RESULTS

On average, using the Skiba 2 model found end W' values different from zero (P = .007; mean ± 95% confidence limit, -2.7 ± 2.0 kJ), with 3 out of 8 cases ending within the predetermined error threshold. Using the Bartram adjustment on average resulted in end W' values that were not different from zero (P = .626; mean ± 95% confidence limit, 0.5 ± 2.5 kJ), with 4 out of 8 cases falling within the predetermined error threshold.

CONCLUSIONS

On average, the Bartram adjustment was an improvement to modeling intermittent work capacity in elite cyclists, with the Skiba 2 model underestimating the rate of W' recovery. In the specific context of modeling team pursuit races, all models were too variable for effective use; hence, individual recovery rates should be explored beyond population-specific rates.

W' Recovery Kinetics after Exhaustion: A Two-Phase Exponential Process Influenced by Aerobic Fitness

PURPOSE

The aims of this study were 1) to model the temporal profile of W' recovery after exhaustion, 2) to estimate the contribution of changing V˙O2 kinetics to this recovery, and 3) to examine associations with aerobic fitness and muscle fiber type (MFT) distribution.

METHODS

Twenty-one men (age = 25 ± 2 yr, V˙O2peak = 54.4 ± 5.3 mL·min-1·kg-1) performed several constant load tests to determine critical power and W' followed by eight trials to quantify W' recovery. Each test consisted of two identical exhaustive work bouts (WB1 and WB2), separated by a variable recovery interval of 30, 60, 120, 180, 240, 300, 600, or 900 s. Gas exchange was measured and muscle biopsies were collected to determine MFT distribution. W' recovery was quantified as observed W' recovery (W'OBS), model-predicted W' recovery (W'BAL), and W' recovery corrected for changing V˙O2 kinetics (W'ADJ). W'OBS and W'ADJ were modeled using mono- and biexponential fitting. Root-mean-square error (RMSE) and Akaike information criterion (∆AICC) were used to evaluate the models' accuracy.

RESULTS

The W'BAL model (τ = 524 ± 41 s) was associated with an RMSE of 18.6% in fitting W'OBS and underestimated W' recovery for all durations below 5 min (P < 0.002). Monoexponential modeling of W'OBS resulted in τ = 104 s with RMSE = 6.4%. Biexponential modeling of W'OBS resulted in τ1 = 11 s and τ2 = 256 s with RMSE = 1.7%. W'ADJ was 11% ± 1.5% lower than W'OBS (P < 0.001). ∆AICC scores favored the biexponential model for W'OBS, but not for W'ADJ. V˙O2peak (P = 0.009) but not MFT distribution (P = 0.303) was associated with W'OBS.

CONCLUSION

We showed that W' recovery from exhaustion follows a two-phase exponential time course that is dependent on aerobic fitness. The appearance of a fast initial recovery phase was attributed to an enhanced aerobic energy provision resulting from changes in V˙O2 kinetics.

W' reconstitution rate at different intensities above critical torque: the role of muscle size and maximal strength

NEW FINDINGS

What is the central question of this study? Do muscle size, maximal force and exercise intensity influence the recovery time constant for the finite impulse above critical torque (τ_IET' )? What is the main finding and its importance? Muscle size and maximal strength have different influences on the parameters of the hyperbolic torque-time to task failure relationship. Greater muscle size and maximal strength, as well as exercise at an intensity of 60% MVC, prolong τ_IET' during intermittent isometric exercise.

ABSTRACT

Muscle perfusion and O₂ delivery limitations through muscle force generation appear to play a major role in defining the hyperbolic torque-time to task failure (T_lim ) relationship. Therefore, we aimed to determine the influence of muscle size and maximal strength on the recovery time constant for the finite impulse above critical torque (τ_IET' ). Ten men participated in the study and performed intermittent isometric tests until task-failure (T_lim ) for the knee-extensors (KE) (35% and 60% maximal voluntary contraction (MVC)) and plantar flexors (PF) (60% MVC). The τ_IET' was determined for each of these T_lim tests using the IET'_BAL model. The IET' (9738 ± 3080 vs. 2959 ± 1289 N m s) and end-test torque (ET)(84.5 ± 7.1 vs. 74.3 ± 12.7 N m) were significantly lower for PF compared to KE (P < 0.05). Exercise tolerance (T_lim ) was significantly longer for PF (239 ± 81 s) than KE (150 ± 55 s) at 60% MVC, and significantly longer for KE at 35% MVC (641 ± 158 s) than 60% MVC. The τ_IET' was significantly faster at 35% MVC (641 ± 177 s) than 60% MVC (1840 ± 354 s) for KE, both of which were significantly slower than PF at 60% MVC (317 ± 102 s). This study showed that τ_IET' during intermittent isometric exercise is slower with greater muscle size and maximal strength.

What is known about the FTP20 test related to cycling? A scoping review

Functional Threshold Power (FTP) in cycling is increasingly used in exercise prescription, particularly with the rise in use of home trainers and virtual exercise platforms. FTP testing does not require biological sampling and is considered a more practical test than others. This scoping review investigated what is known about the 20-minute FTP (FTP²⁰) test. A three-step search strategy was used to identify studies in relevant databases (PubMed, CINAHL, SportDiscus, Google Scholar, Web of Science) and grey literature. Data were extracted and common themes identified which allowed for descriptive analysis and thematic summary. Fifteen studies were included. The primary focus fitted broadly into four themes: reliability, association with other physiological markers, other power-related concepts and performance prediction. The FTP²⁰ test was reported as a reliable test. Studies investigating the relationship of FTP²⁰ with other physiological markers and power-related concepts reported large limits of agreement suggesting parameters cannot be used interchangeably. Some findings indicate that FTP²⁰ may be useful in performance prediction. The majority of studies involved trained male cyclists. Overall, existing literature on the FTP²⁰ test is limited. Further investigation is needed to provide physiological justification for FTP²⁰ and inform use in exercise prescription in a range of populations.

One-Week High-Dose β-Alanine Loading Improves World Tour Cyclists' Time-Trial Performance

Supplementation with β-alanine is becoming a common practice in high-performance athletes. The purpose of the present study was to investigate the effects of a one-week high-dose β-alanine loading phase employing a sustained-release powder on preserving the time-trial performance capacity of world tour cyclists during overreaching training. Per day, 20 g of sustained-release β-alanine was administered during one week (7 days) of intensive team training camp in a randomised balanced placebo-controlled parallel trial design, with six participants in each β-alanine (BA) or placebo (PLA) group. A 10-min time trial (10′ TT) was carried out to analyse performance and biochemical variables. Anthropometry, paresthesia, and adverse event data were also collected. Power-based relative training load was quantified. Compared to placebo, the BA improved mean power (6.21%, 37.23 W; 95% CI: 3.98–70.48 W, p = 0.046), distance travelled (2.16%, p = 0.046) and total work (4.85%, p = 0.046) without differences in cadence (p = 0.506) or RPE. Lactate (p = 0.036) and anion gap (p = 0.047) were also higher in the BA group, without differences in pH or Bicarbonate. High daily and single doses were well tolerated. One-week high-dose β-alanine loading with a sustained-release powder blend can help attenuate 10′ TT performance losses of world tour cyclists due to intensive training.

Exercise Intensity and Pacing Pattern During a Cross-Country Olympic Mountain Bike Race

Objective: To examine the power profiles and pacing patterns in relation to critical power (CP) and maximal aerobic power (MAP) output during a cross-country Olympic (XCO) mountain bike race.

Methods: Five male and two female national competitive XCO cyclists completed a UCI Cat. 1 XCO race. The races were 19 km and 23 km and contained five (female) and six (male) laps, respectively. Power output (PO) during the race was measured with the cyclists’ personal power meters. On two laboratory tests using their own bikes and power meters, CP and work capacity above CP (W') were calculated using three time trials of 12, 7, and 3 min, while MAP was established based on a 3-step submaximal test and the maximal oxygen uptake from the 7-min time trial.

Results: Mean PO over the race duration (96 ± 7 min) corresponded to 76 ± 9% of CP and 63 ± 4% of MAP. 40 ± 8% of race time was spent with PO > CP, and the mean duration and magnitude of the bouts >CP was ~8 s and ~120% of CP. From the first to last lap, time >CP and accumulated W' per lap decreased with 9 ± 6% and 45 ± 17%, respectively. For single >CP bouts, mean magnitude and mean W' expended decreased by 25 ± 8% and 38 ± 15% from the first to the last lap, respectively. Number and duration of bouts did not change significantly between laps.

Conclusion: The highly variable pacing pattern in XCO implies the need for rapid changes in metabolic power output, as a result of numerous separate short-lived >CP actions which decrease in magnitude in later laps, but with little lap-to-lap variation in number and duration.

A new energetics model for the assessment of the power-duration relationship during over-ground running

We evaluated the reliability of an over-ground running three-minute all-out test (3MT) and compared this to traditional multiple-visit testing to determine the critical speed (CS) and distance > CS (D´). Using a novel energetics model during the 3MT, critical power (CP) and work > CP (W´) were also evaluated for reliability and compared to the multiple-visit tests. Over-ground running speed was measured using Global Positioning Systems during fixed-speed trials on a 400 m track to exhaustion, at four intensities corresponding to: (i) maximal oxygen uptake (V˙O2max) (V_max), (ii) 110% V˙O2max(110%Vmax), (iii) Δ70% (i.e. 70% of the difference between gas exchange threshold and V_max) and (iv) Δ85%. The participants subsequently performed the 3MT across two days to determine its reliability. There were no differences between the multiple-visit testing and the 3MT for CS (P = 0.328) and D´ (P = 0.919); however, CP (P = 0.02) and W´ (P < 0.001) were higher in the 3MT. The reliability of the 3MT was stable (P > 0.05) between trials for all variables, with coefficient of variation ranging from 2.0-8.1%. The current over-ground energetics model can reliably estimate CP and W´ based on GPS speed data during the 3MT, which supports its use for most athletic training and monitoring purposes. The reliability of the over-ground running 3MT for power- and speed-related indices was sufficient to detect typical training adaptations; however, it may overestimate CP (∼ 25 W) and W´ (∼ 7 kJ) compared to multiple-visit tests.

W' Reconstitution Accelerates More with Decreasing Intensity in the Heavy- versus the Moderate-Intensity Domain

INTRODUCTION

The purpose of this study was to investigate the effect of the recovery intensity domain on W' reconstitution. We used the W'BAL model as a framework and tested its predictive capabilities (W'PRED) across the different intensity domains.

METHODS

Twelve young men (51.7 ± 5.9 mL·kg-1·min-1) completed a ramp incremental test, three to five constant power output (PO) tests to determine critical power (CP) and W', and minimally two trials to verify the maximal lactate (La-) steady state. During four experimental trials, subjects performed two work bouts (WB1 and WB2) at P6 (i.e., PO that predicts exhaustion within 6 min) separated by a recovery interval at CP-10 W, Δgas exchange threshold (GET)-CP, GET, and 50% GET, respectively. WB1 was designed to deplete 75% W', and the recovery time varied to replenish 50% W'. WB2 was performed to exhaustion (W'ACT). W'PRED was compared with W'ACT to evaluate the accuracy of the W'BAL model. Excess postexercise oxygen consumption was calculated as the difference between the measured and the predicted oxygen uptake during recovery.

RESULTS

W'ACT averaged 49% ± 24%, 69% ± 24%, 81% ± 28%, and 93% ± 21% for CP-10 W, ΔGET-CP, GET, and 50% GET, respectively (P = 0.002). W'PRED overestimated W'ACT in CP-10 W (34% ± 32%, P = 0.004) and underestimated W'ACT in 50% GET (24% ± 28%, P = 0.013). Excess postexercise oxygen consumption was lowest in CP-10 W (P < 0.01) and higher in GET compared with ΔGET-CP (P = 0.01).

CONCLUSION

We demonstrated that W'PRED overestimated and underestimated W'ACT in the heavy- and moderate-intensity domain, respectively. Therefore, the practical applicability of a single recovery time constant, which only relies on the difference between the recovery PO and the CP, is questionable.

The balance of muscle oxygen supply and demand reveals critical metabolic rate and predicts time to exhaustion

We tested the hypothesis that during whole body exercise, the balance between muscle O₂ supply and metabolic demand may elucidate intensity domains, reveal a critical metabolic rate, and predict time to exhaustion. Seventeen active, healthy volunteers (12 males, 5 females; 32 ± 2 yr) participated in two distinct protocols. Study 1 (n = 7) consisted of constant work rate cycling in the moderate, heavy, and severe exercise intensity domains with concurrent measures of pulmonary V̇o₂ and local %SmO₂ [via near-infrared spectroscopy (NIRS)] on quadriceps and forearm sites. Average %SmO₂ at both sites displayed a domain-dependent response (P < 0.05). A negative %SmO₂ slope was evident during severe-domain exercise but was positive during exercise below critical power (CP) at both muscle sites. In study 2 (n = 10), quadriceps and forearm site %SmO₂ was measured during three continuous running trials to exhaustion and three intermittent intensity (ratio = 60 s severe: 30 s lower intensity) trials to exhaustion. Intensity-dependent negative %SmO₂ slopes were observed for all trials (P < 0.05) and predicted zero slope at critical velocity. %SmO₂ accurately predicted depletion and repletion of %D' balance on a second-by-second basis (R² = 0.99, P < 0.05; both sites). Time to exhaustion predictions during continuous and intermittent exercise were either not different or better with %SmO₂ [standard error of the estimate (SEE) < 20.52 s for quad, <44.03 s for forearm] versus running velocity (SEE < 65.76 s). Muscle O₂ balance provides a dynamic physiological delineation between sustainable and unsustainable exercise (consistent with a "critical metabolic rate") and predicts real-time depletion and repletion of finite work capacity and time to exhaustion.NEW & NOTEWORTHY Dynamic muscle O₂ saturation discriminates boundaries between exercise intensity domains, exposes a critical metabolic rate as the highest rate of steady state O₂ supply and demand, describes time series depletion and repletion for work above critical power, and predicts time to exhaustion during severe domain whole body exercise. These results highlight the matching of O₂ supply and demand as a primary determinant for sustainable exercise intensities from those that are unsustainable and lead to exhaustion.

The Aerobic and Anaerobic Contribution During Repeated 30-s Sprints in Elite Cyclists

Although the ability to sprint repeatedly is crucial in road cycling races, the changes in aerobic and anaerobic power when sprinting during prolonged cycling has not been investigated in competitive elite cyclists. Here, we used the gross efficiency (GE)-method to investigate: (1) the absolute and relative aerobic and anaerobic contributions during 3 × 30-s sprints included each hour during a 3-h low-intensity training (LIT)-session by 12 cyclists, and (2) how the energetic contribution during 4 × 30-s sprints is affected by a 14-d high-volume training camp with (SPR, n = 9) or without (CON, n = 9) inclusion of sprints in LIT-sessions. The aerobic power was calculated based on GE determined before, after sprints, or the average of the two, while the anaerobic power was calculated by subtracting the aerobic power from the total power output. When repeating 30-s sprints, the mean power output decreased with each sprint (p < 0.001, ES:0.6-1.1), with the majority being attributed to a decrease in mean anaerobic power (first vs. second sprint: -36 ± 15 W, p < 0.001, ES:0.7, first vs. third sprint: -58 ± 16 W, p < 0.001, ES:1.0). Aerobic power only decreased during the third sprint (first vs. third sprint: -17 ± 5 W, p < 0.001, ES:0.7, second vs. third sprint: 16 ± 5 W, p < 0.001, ES:0.8). Mean power output was largely maintained between sets (first set: 786 ± 30 W vs. second set: 783 ± 30 W, p = 0.917, ES:0.1, vs. third set: 771 ± 30 W, p = 0.070, ES:0.3). After a 14-d high-volume training camp, mean power output during the 4 × 30-s sprints increased on average 25 ± 14 W in SPR (p < 0.001, ES:0.2), which was 29 ± 20 W more than CON (p = 0.008, ES: 0.3). In SPR, mean anaerobic power and mean aerobic power increased by 15 ± 13 W (p = 0.026, ES:0.2) and by 9 ± 6 W (p = 0.004, ES:0.2), respectively, while both were unaltered in CON. In conclusion, moderate decreases in power within sets of repeated 30-s sprints are primarily due to a decrease in anaerobic power and to a lesser extent in aerobic power. However, the repeated sprint-ability (multiple sets) and corresponding energetic contribution are maintained during prolonged cycling in elite cyclists. Including a small number of sprints in LIT-sessions during a 14-d training camp improves sprint-ability mainly through improved anaerobic power.

The Acute Physiological and Perceptual Effects of Individualizing the Recovery Interval Duration Based Upon the Resolution of Muscle Oxygen Consumption During Cycling Exercise

PURPOSE

There has been paucity in research investigating the individualization of recovery interval duration during cycling-based high-intensity interval training (HIIT). The main aim of the study was to investigate whether individualizing the duration of the recovery interval based upon the resolution of muscle oxygen consumption would improve the performance during work intervals and the acute physiological response of the HIIT session, when compared with a standardized (2:1 work recovery ratio) approach.

METHODS

A total of 16 well-trained cyclists (maximal oxygen consumption: 60 [7] mL·kg-1·min-1) completed 6 laboratory visits: (Visit 1) incremental exercise test, (Visit 2) determination of the individualized (IND) recovery duration, using the individuals' muscle oxygen consumption recovery duration to baseline from a 4- and 8-minute work interval, (Visits 3-6) participants completed a 6 × 4- and a 3 × 8-minute HIIT session twice, using the IND and standardized recovery intervals.

RESULTS

Recovery duration had no effect on the percentage of the work intervals spent at >90% and >95% of maximal oxygen consumption, maximal minute power output, and maximal heart rate, during the 6 × 4- and 3 × 8-minute HIIT sessions. Recovery duration had no effect on mean work interval power output, heart rate, oxygen consumption, blood lactate, and rating of perceived exertion. There were no differences in reported session RPE between recovery durations for the 6 × 4- and 3 × 8-minute HIIT sessions.

CONCLUSION

Individualizing HIIT recovery duration based upon the resolution of muscle oxygen consumption to baseline levels does not improve the performance of the work intervals or the acute physiological response of the HIIT session, when compared with standardized recovery duration.

Critical oxygenation: Can muscle oxygenation inform us about critical power?

The power-duration relationship is well documented for athletic performance and is formulated out mathematically in the critical power (CP) model. The CP model, when applied properly, has great predictive power, e.g. pedaling at a specific power output on an ergometer the model precisely calculates the time over which an athlete can sustain this power. However, CP presents physiological inconsistencies and process-oriented problems. The rapid development of near-infrared spectroscopy (NIRS) to measure muscle oxygenation (SmO₂) dynamics provides a physiological exploration of the CP model on a conceptual and empirical level. Conceptually, the CP model provides two components: first CP is defined as the highest metabolic rate that can be achieved through oxidative means. And second, work capacity above CP named W'. SmO₂ presents a steady-state in oxygen supply and demand and thereby represents CP specifically at a local level of analysis. Empirically, exploratory data quickly illustrates the relationship between performance and SmO₂, as shown during 3-min all-out cycling tests to assess CP. During these tests, performance and SmO₂ essentially mirror each other, and both CP and W' generate solid correlation with what would be deemed their SmO₂ counterparts: first, the steady-state of SmO₂ correlates with CP. And second, the tissue oxygen reserve represented in SmO₂, when calculated as an integral corresponds to W'. While the empirical data presented is preliminary, the proposition of a concurring physiological model to the current CP model is a plausible inference. Here we propose that SmO₂ steady-state representing CP as critical oxygenation or CO. And the tissue oxygen reserve above CO would then be identified as O'. This new CO model could fill in the physiological gap between the highly predictive CP model and at times its inability to track human physiology consistently. For simplicity's sake, this would include acute changes in physiology as a result of changing climate or elevation with travel, which can affect performance. These types of acute fluctuations, but not limited to, would be manageable when applying a CO model in conjunction with the CP model. Further, modeling is needed to investigate the true potential of NIRS to model CP, with a focus on repeatability, recovery, and systemic vs local workloads.

Effect of Running Velocity Variation on the Aerobic Cost of Running

The aerobic cost of running (CR), an important determinant of running performance, is usually measured during constant speed running. However, constant speed does not adequately reflect the nature of human locomotion, particularly competitive races, which include stochastic variations in pace. Studies in non-athletic individuals suggest that stochastic variations in running velocity produce little change in CR. This study was designed to evaluate whether variations in running speed influence CR in trained runners. Twenty competitive runners (12 m, VO2max = 73 ± 7 mL/kg; 8f, VO2max = 57 ± 6 mL/kg) ran four 6-minute bouts at an average speed calculated to require ~90% ventilatory threshold (VT) (measured using both v-slope and ventilatory equivalent). Each interval was run with minute-to-minute pace variation around average speed. CR was measured over the last 2 min. The coefficient of variation (CV) of running speed was calculated to quantify pace variations: ±0.0 m∙s-1 (CV = 0%), ±0.04 m∙s-1 (CV = 1.4%), ±0.13 m∙s-1(CV = 4.2%), and ±0.22 m∙s-1(CV = 7%). No differences in CR, HR, or blood lactate (BLa) were found amongst the variations in running pace. Rating of perceived exertion (RPE) was significantly higher only in the 7% CV condition. The results support earlier studies with short term (3s) pace variations, that pace variation within the limits often seen in competitive races did not affect CR when measured at running speeds below VT.

Power Profiling in U23 Professional Cyclists During a Competitive Season

PURPOSE

The aim of this study was to investigate changes in the power profile of U23 professional cyclists during a competitive season based on maximal mean power output (MMP) and derived critical power (CP) and work capacity above CP (W') obtained during training and racing.

METHODS

A total of 13 highly trained U23 professional cyclists (age = 21.1 [1.2] y, maximum oxygen consumption = 73.8 [1.9] mL·kg-1·min-1) participated in this study. The cycling season was split into pre-season and in-season. In-season was divided into early-, mid-, and late-season periods. During pre-season, a CP test was completed to derive CPtest and W'test. In addition, 2-, 5-, and 12-minute MMP during in-season were used to derive CPfield and W'field.

RESULTS

There were no significant differences in absolute 2-, 5-, and 12-minute MMP, CPfield, and W'field between in-season periods. Due to changes in body mass, relative 12-minute MMP was higher in late-season compared with early-season (P = .025), whereas relative CPfield was higher in mid- and late-season (P = .031 and P = .038, respectively) compared with early-season. There was a strong correlation (r = .77-.83) between CPtest and CPfield in early- and mid-season but not late-season. Bland-Altman plots and standard error of estimates showed good agreement between CPtest and in-season CPfield but not between W'test and W'field.

CONCLUSION

These findings reveal that the power profile remains unchanged throughout the in-season, except for relative 12-minute MMP and CPfield in late-season. One pre-season and one in-season CP test are recommended to evaluate in-season CPfield and W'field.

Summated Hazard Score as a Powerful Predictor of Fatigue in Relation to Pacing Strategy

During competitive events, the pacing strategy depends upon how an athlete feels at a specific moment and the distance remaining. It may be expressed as the Hazard Score (HS) with momentary HS being shown to provide a measure of the likelihood of changing power output (PO) within an event and summated HS as a marker of how difficult an event is likely to be perceived to be. This study aimed to manipulate time trial (TT) starting strategies to establish whether the summated HS, as opposed to momentary HS, will improve understanding of performance during a simulated cycling competition. Seven subjects (peak PO: 286 ± 49.7 W) performed two practice 10-km cycling TTs followed by three 10-km TTs with imposed PO (±5% of mean PO achieved during second practice TT and a self-paced TT). PO, rating of perceived exertion (RPE), lactate, heart rate (HR), HS, summated HS, session RPE (sRPE) were collected. Finishing time and mean PO for self-paced (time: 17.51 ± 1.41 min; PO: 234 ± 62.6 W), fast-start (time: 17.72 ± 1.87 min; PO: 230 ± 62.0 W), and slow-start (time: 17.77 ± 1.74 min; PO: 230 ± 62.7) TT were not different. There was a significant interaction between each secondary outcome variable (PO, RPE, lactate, HR, HS, and summated HS) for starting strategy and distance. The evolution of HS reflected the imposed starting strategy, with a reduction in PO following a fast-start, an increased PO following a slow-start with similar HS during the last part of all TTs. The summated HS was strongly correlated with the sRPE of the TTs (r = 0.88). The summated HS was higher with a fast start, indicating greater effort, with limited time advantage. Thus, the HS appears to regulate both PO within a TT, but also the overall impression of the difficulty of a TT.

Neuromuscular responses to fatiguing locomotor exercise

Over the last two decades, an abundance of research has explored the impact of fatiguing locomotor exercise on the neuromuscular system. Neurostimulation techniques have been implemented prior to and following locomotor exercise tasks of a wide variety of intensities, durations, and modes. These techniques have allowed for the assessment of alterations occurring within the central nervous system and the muscle, while techniques such as transcranial magnetic stimulation and spinal electrical stimulation have permitted further segmentalization of locomotor exercise-induced changes along the motor pathway. To this end, the present review provides a comprehensive synopsis of the literature pertaining to neuromuscular responses to locomotor exercise. Sections of the review were divided to discuss neuromuscular responses to maximal, severe, heavy and moderate intensity, high-intensity intermittent exercise, and differences in neuromuscular responses between exercise modalities. During maximal and severe intensity exercise, alterations in neuromuscular function reside primarily within the muscle. Although post-exercise reductions in voluntary activation following maximal and severe intensity exercise are generally modest, several studies have observed alterations occurring at the cortical and/or spinal level. During prolonged heavy and moderate intensity exercise, impairments in contractile function are attenuated with respect to severe intensity exercise, but are still widely observed. While reductions in voluntary activation are greater during heavy and moderate intensity exercise, the specific alterations occurring within the central nervous system remain unclear. Further work utilizing stimulation techniques during exercise and integrating new and emerging techniques such as high-density electromyography is warranted to provide further insight into neuromuscular responses to locomotor exercise.

Oxygen Demand, Uptake, and Deficits in Elite Cross-Country Skiers during a 15-km Race

PURPOSE

This study aimed to quantify the repeated oxygen deficits attained during intermittent endurance exercise by measuring oxygen consumption (V˙O2) and oxygen demand (V˙O2) throughout a simulated roller ski race.

METHODS

Eight male elite cross-country skiers (V˙O2peak, 77.4 ± 4.4 mL·kg⋅min) raced a 13.5-km roller ski time trial on a World Cup course. On two additional days, athletes completed (i) six submaximal loads (~5 min) and ~4-min maximal trial to establish athlete-specific estimates of skiing economy, V˙O2peak, and maximal ΣO2 (MAOD); and (ii) a simulation of the time trial on a roller skiing treadmill. During the simulation, external work rate (Pprop) and skiing speed (v) were adjusted to match the Pprop and v measured during the time trial, and pulmonary V˙O2 was measured breath by breath. V˙O2 and ΣO2 were calculated using an athlete-specific model for skiing economy throughout the treadmill simulation.

RESULTS

During the treadmill simulation, V˙O2 was on average 0.77 V˙O2peak, and active V˙O2 (i.e., excluding the time in simulated downhill) was on average 1.01 V˙O2peak. The athletes repeatedly attained substantial oxygen deficits in individual uphill sections of the treadmill simulation, but the deficits were typically small compared with their MAOD (average 14%, range ~0%-50%). However, the ΣO2 summed over all periods of active propulsion was on average 3.8 MAOD.

CONCLUSION

Athletes repeatedly attain substantial oxygen deficits in the uphill segments of a distance cross-country ski race. Furthermore, the total accumulated oxygen deficit of all these segments is several times higher than the athletes' MAOD. This suggests that the rapid recovery of the energy stores represented by the oxygen deficit is necessary during downhill sections, and that this might be an important determinant of distance skiing performance.

Modeling the depletion and reconstitution of W': Effects of prior exercise on cycling tolerance

Thirteen healthy male subjects (age 28 ± 7 years) performed tests for critical power and W' determination and two square-wave high-intensity exercises until exhaustion either with prior very-heavy intensity cycling (EXP) or without (CON). Prior exercise bout induced a depletion of 60 % of W'. After 10 min of recovery, W' reconstitution was not fully achieved (∼ 92 %). Time to exhaustion and Δ blood lactate concentration were significantly lower in EXP compared to CON (595 ± 118 s vs. 683 ± 148 s; 3.5 ± 1.2 mmol.L^-1 vs. 8.8 ± 2.3 mmol.L^-1; p < 0.05, respectively). Oxygen uptake (VO₂) and heart rate were significantly higher in EXP, during the first 150 s of exercise (p < 0.05). The carbon dioxide production kinetics was significantly slower in EXP (mean response time = 87.8 ± 17.8 s vs. 73.7 ± 16.6 s in CON; p < 0.05). Thus, prior exercise impairs high-intensity cycling performance which can partly be explained by physiological disturbances linked to W' depletion.

Moving forward with backward pedaling: a review on eccentric cycling

PURPOSE

There is a profound gap in the understanding of the eccentric cycling intensity continuum, which prevents accurate exercise prescription based on desired physiological responses. This may underestimate the applicability of eccentric cycling for different training purposes. Thus, we aimed to summarize recent research findings and screen for possible new approaches in the prescription and investigation of eccentric cycling.

METHOD

A search for the most relevant and state-of-the-art literature on eccentric cycling was conducted on the PubMed database. Literature from reference lists was also included when relevant.

RESULTS

Transversal studies present comparisons between physiological responses to eccentric and concentric cycling, performed at the same absolute power output or metabolic load. Longitudinal studies evaluate responses to eccentric cycling training by comparing them with concentric cycling and resistance training outcomes. Only one study investigated maximal eccentric cycling capacity and there are no investigations on physiological thresholds and/or exercise intensity domains during eccentric cycling. No study investigated different protocols of eccentric cycling training and the chronic effects of different load configurations.

CONCLUSION

Describing physiological responses to eccentric cycling based on its maximal exercise capacity may be a better way to understand it. The available evidence indicates that clinical populations may benefit from improvements in aerobic power/capacity, exercise tolerance, strength and muscle mass, while healthy and trained individuals may require different eccentric cycling training approaches to benefit from similar improvements. There is limited evidence regarding the mechanisms of acute physiological and chronic adaptive responses to eccentric cycling.

The Application of Critical Power, the Work Capacity above Critical Power (W'), and its Reconstitution: A Narrative Review of Current Evidence and Implications for Cycling Training Prescription

The two-parameter critical power (CP) model is a robust mathematical interpretation of the power–duration relationship, with CP being the rate associated with the maximal aerobic steady state, and W′ the fixed amount of tolerable work above CP available without any recovery. The aim of this narrative review is to describe the CP concept and the methodologies used to assess it, and to summarize the research applying it to intermittent cycle training techniques. CP and W′ are traditionally assessed using a number of constant work rate cycling tests spread over several days. Alternatively, both the 3-min all-out and ramp all-out protocols provide valid measurements of CP and W′ from a single test, thereby enhancing their suitability to athletes and likely reducing errors associated with the assumptions of the CP model. As CP represents the physiological landmark that is the boundary between heavy and severe intensity domains, it presents several advantages over the de facto arbitrarily defined functional threshold power as the basis for cycle training prescription at intensities up to CP. For intensities above CP, precise prescription is not possible based solely on aerobic measures; however, the addition of the W′ parameter does facilitate the prescription of individualized training intensities and durations within the severe intensity domain. Modelling of W′ reconstitution extends this application, although more research is needed to identify the individual parameters that govern W′ reconstitution rates and their kinetics.

High-intensity decreasing interval training (HIDIT) increases time above 90% [Formula: see text]O2peak

Purpose

Training near \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}$$\end{document}V˙O₂max is considered to be the most effective way to enhance \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}$$\end{document}V˙O₂max. High-intensity interval training (HIIT) is a well-known time-efficient training method for improving cardiorespiratory and metabolic function and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}$$\end{document}V˙O₂max. While long HIIT bouts allow \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}$$\end{document}V˙O₂max to be achieved quickly, short HIIT bouts improve time to exhaustion (Tlim). The aim of this study was to evaluate the time spent above 90% \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}$$\end{document}V˙O₂peak (T > 90% \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}$$\end{document}V˙O₂peak) during three different HIIT protocols.

Methods

Twelve cyclists performed three HIIT sessions. Each protocol had the same work and recovery power and ratio of work·recovery⁻¹. The protocols consisted of long-interval HIIT (LI_HIIT, 3 min work—2 min recovery), short-interval HIIT (SI_HIIT, 30 s work—20 s recovery), and high-intensity decreasing interval training (HIDIT, work from 3 min to 30 s and recovery from 2 min to 20 s). T > 90% \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}$$\end{document}V˙O₂peak, Tlim, blood lactate [La], and rate of perceived exertion (RPE) were measured at Tlim.

Results

T > 90% \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}$$\end{document}V˙O₂peak was greater in HIDIT (312 ± 207 s) than in SI_HIIT (182 ± 225 s; P = 0.036) or LI_HIIT (179 ± 145 s; P = 0.027). Tlim was not significantly different (P > 0.05) between HIDIT (798 ± 185 s), SI_HIIT (714 ± 265 s), and LI_HIIT (664 ± 282). At Tlim, no differences in [La] and RPE were found between protocols (P > 0.05).

Conclusion

HIDIT showed the highest T > 90% \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}$$\end{document}V˙O₂peak, suggesting that it may be a good strategy to increase time close to \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}$$\end{document}V˙O₂peak, despite similar Tlim, [La], and RPE at Tlim.

Physiological and anthropometric determinants of critical power, W' and the reconstitution of W' in trained and untrained male cyclists

Purpose

This study examined the relationship of physiological and anthropometric characteristics with parameters of the critical power (CP) model, and in particular the reconstitution of W′ following successive bouts of maximal exercise, amongst trained and untrained cyclists.

Methods

Twenty male adults (trained nine; untrained 11; age 39 ± 15 year; mass 74.7 ± 8.7 kg; V̇O_2max 58.0 ± 8.7 mL kg⁻¹ min⁻¹) completed three incremental ramps (20 W min⁻¹) to exhaustion interspersed with 2-min recoveries. Pearson’s correlation coefficients were used to assess relationships for W′ reconstitution after the first recovery (W′_rec1), the delta in W′ reconstituted between recoveries (∆W′_rec)_, CP and W′.

Results

CP was strongly related to V̇O_2max for both trained (r = 0.82) and untrained participants (r = 0.71), whereas W′ was related to V̇O_2max when both groups were considered together (r = 0.54). W′_rec1 was strongly related to V̇O_2max for the trained (r = 0.81) but not untrained (r = 0.18); similarly, ∆W′_rec was strongly related to V̇O_2max (r = − 0.85) and CP (r = − 0.71) in the trained group only.

Conclusions

Notable physiological relationships between parameters of aerobic fitness and the measurements of W′ reconstitution were observed, which differed among groups. The amount of W′ reconstitution and the maintenance of W′ reconstitution that occurred with repeated bouts of maximal exercise were found to be related to key measures of aerobic fitness such as CP and V̇O_2max. This data demonstrates that trained cyclists wishing to improve their rate of W′ reconstitution following repeated efforts should focus training on improving key aspects of aerobic fitness such as V̇O_2max and CP.