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 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 ten experimental trials to quantify W' depletion. Each experimental trial consisted of two constant load work bouts (WB1 + WB2) interspersed by a recovery interval. WB1 was designed to evoke a 25% or 75% W' depletion (DEP 25% + DEP 75% ). Subsequently, participants recovered for 30, 60, 120, 300 or 600 s, and then performed WB2 to exhaustion in order to calculate the observed W' recovery (W' OBS ). W' OBS data were fitted using monoexponential and biexponential models, both with a variable and a fixed model amplitude. Root mean square error (RMSE) 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 RMSE values (0.4-5.0%) compared to the monoexponential models (2.9-8.0%). However, ΔAIC c resulted in negative values (-15.5 and -23.3) for the model fits where the amplitude was 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 , CP and GET ( r = 0.67-0.77). CONCLUSIONS: The present study results did not provide evidence in favor of a biexponential modeling technique to characterize W' recovery following partial depletion. Moreover, we demonstrated that fixed t values 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 t values in future predictive W' models.

Training Load and Acute Performance Decrements Following Different Training Sessions.

PURPOSE: To examine the differences in training load (TL) metrics when quantifying training sessions differing in intensity and duration. The relationship between the TL metrics and the acute performance decrement measured immediately after the sessions was also assessed. METHODS: Eleven male recreational cyclists performed 4 training sessions in a random order, immediately followed by a 3-km time trial (TT). Before this period, participants performed the time TT in order to obtain a baseline performance. The difference in the average power output for the TTs following the training sessions was then expressed relative to the best baseline performance. The training sessions were quantified using 7 different TL metrics, 4 using heart rate as input, 2 using power output, and 1 using the rating of perceived exertion. RESULTS: The load of the sessions was estimated differently depending on the TL metrics used. Also, within the metrics using the same input (heart rate and power), differences were found. TL using the rating of perceived exertion was the only metric showing a response that was consistent with the acute performance decrements found for the different training sessions. The Training Stress Score and the individualized training impulse demonstrated similar patterns but overexpressed the intensity of the training sessions. The total work done resulted in an overrepresentation of the duration of training. CONCLUSION: TL metrics provide dissimilar results as to which training sessions have higher loads. The load based on TL using the rating of perceived exertion was the only one in line with the acute performance decrements found in this study.

The Fitness-Fatigue Model: What's in the Numbers?

PURPOSE: The purpose of this commentary is to outline some of the pitfalls when using the fitness-fatigue model to unravel the interaction between training load and performance. By doing so, we encourage sport scientists and coaches to interpret the parameters from the model with some extra caution. CONCLUSIONS: Caution is needed when interpreting the fitness-fatigue model since the parameter values are influenced by the starting parameter values, the modeling technique, and the input of the model. Also, the use of general constants should be avoided since they do not account for interindividual differences and differences between training-load methods. Therefore, we advise sport scientists and coaches to use the model as a way to work more data-informed rather than working data-driven.

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.

The Influence of Different Training Load Quantification Methods on the Fitness-Fatigue Model.

PURPOSE: Numerous methods exist to quantify training load (TL). However, the relationship with performance is not fully understood. Therefore the purpose of this study was to investigate the influence of the existing TL quantification methods on performance modeling and the outcome parameters of the fitness-fatigue model. METHODS: During a period of 8 weeks, 9 subjects performed 3 interval training sessions per week. Performance was monitored weekly by means of a 3-km time trial on a cycle ergometer. After this training period, subjects stopped training for 3 weeks but still performed a weekly time trial. For all training sessions, Banister training impulse (TRIMP), Lucia TRIMP, Edwards TRIMP, training stress score, and session rating of perceived exertion were calculated. The fitness-fatigue model was fitted for all subjects and for all TL methods. RESULTS: The error in relating TL to performance was similar for all methods (Banister TRIMP: 618 [422], Lucia TRIMP: 625 [436], Edwards TRIMP: 643 [465], training stress score: 639 [448], session rating of perceived exertion: 558 [395], and kilojoules: 596 [505]). However, the TL methods evolved differently over time, which was reflected in the differences between the methods in the calculation of the day before performance on which training has the biggest positive influence (range of 19.6 d). CONCLUSIONS: The authors concluded that TL methods cannot be used interchangeably because they evolve differently.

Ramp vs. step tests: valid alternatives to determine the maximal lactate steady-state intensity?

PURPOSE: The aims of this study were (1) to investigate if the respiratory compensation point (RCP) as derived from ramp incremental (RI) exercise could accurately predict the power output (PO) at the maximal lactate steady state (MLSS), and (2) to compare its accuracy with the second lactate threshold (LT2) obtained from step incremental (SI) exercise. METHODS: Nineteen participants performed a RI test (30 W·min-1) to determine RCP, a SI test (30 or 40 W·3 min-1) to determine LT2, and two or more constant work rate (CWR) tests to determine MLSS. For each participant, the [Formula: see text]O2/PO relationship for RI and CWR exercise was established. The ramp-identified PO at RCP was corrected by accounting for the gap between these relationships using the individually determined [Formula: see text] O2/PO regression above GET (RCPcorr-1) or using a fixed regression slope (RCPcorr-2). LT2 was determined using four methods: Dmax, modified Dmax (ModDmax), 4-mM threshold (LT4mM) and an expert-determined LT2 (LT2-expert). RESULTS: RCPcorr-1 (235 ± 69 W), RCPcorr-2 (228 ± 58 W) and LT2-expert (227 ± 61 W) were not different from MLSS (225 ± 60 W). Dmax (203 ± 53 W) underestimated MLSS, while RCP (280 ± 60 W), ModDmax (235 ± 67 W) and LT4mM (234 ± 68 W) overestimated MLSS. The [Formula: see text]O2 at RCP (3.13 ± 0.79L·min-1) and LT2-expert (2.99 ± 0.19L·min-1) did not differ from MLSS (3.05 ± 0.72 L·min-1). CONCLUSION: This study demonstrated that RCP as derived from RI exercise and LT2 as derived from SI exercise can be equally accurate to determine the PO associated with MLSS. Although these results confirmed the suitability of RI and SI tests for this purpose, they also highlighted the importance of an appropriate threshold method selection and the eye of the expert.

Training Progression in Recreational Cyclists: No Linear Dose-Response Relationship With Training Load.

ABSTRACT: Vermeire, KM, Vandewiele, G, Caen, K, Lievens, M, Bourgois, JG, and Boone, J. Training progression in recreational cyclists: no linear dose-response relationship with training load. J Strength Cond Res 35(12): 3500-3505, 2021-The purpose of the study was to assess the relationship between training load (TL) and performance improvement in a homogeneous group of recreational cyclists, training with a self-oriented training plan. Training data from 11 recreational cyclists were collected over a 12-week period. Before and after the training period, subjects underwent a laboratory incremental exercise test with blood lactate measurements to determine the power output associated with the aerobic threshold (PAT) and the anaerobic threshold (PANT), and the maximal power output (PMAX) was also determined. Mean weekly TL (calculated using the training impulse (TRIMP) of Banister, Edwards TRIMP, Lucia TRIMP and the individualized TRIMP) were correlated to the progression in fitness parameters using Pearson Correlation. Training intensity distribution (TID) was also determined (% in zone 1 as ANT). No significant correlations between mean weekly TRIMP values and the improvement on PMAX (r = -0.22 to 0.08), PANT (r = -0.56 to -0.31) and PAT (r = -0.08 to 0.41) were found. The TID was significant in a multiple regression with PANT as dependent variable (y = 0.0088 + 0.1094 × Z1 - 0.2704 × Z2 + 1.0416 × Z3; p = 0.02; R2 = 0.62). In conclusion, this study shows that the commonly used TRIMP methods to quantify TL do not show a linear dose-response relationship with performance improvement in recreational cyclists. Furthermore, the study shows that TID might be a key factor to establish a relationship with performance improvement.

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.

Aerobic Interval Training Impacts Muscle and Brain Oxygenation Responses to Incremental Exercise.

The purpose of the present study was to assess the effects of aerobic interval training on muscle and brain oxygenation to incremental ramp exercise. Eleven physically active subjects performed a 6-week interval training period, proceeded and followed by an incremental ramp exercise to exhaustion (25 W min-1). Throughout the tests pulmonary gas exchange and muscle (Vastus Lateralis) and brain (prefrontal cortex) oxygenation [concentration of deoxygenated and oxygenated hemoglobin, HHb and O2Hb, and tissue oxygenation index (TOI)] were continuously recorded. Following the training intervention V . ⁢ O 2 peak had increased with 7.8 ± 5.0% (P < 0.001). The slope of the decrease in muscle TOI had decreased (P = 0.017) 16.6 ± 6.4% and the amplitude of muscle HHb and totHb had increased (P < 0.001) 40.4 ± 15.8 and 125.3 ± 43.1%, respectively. The amplitude of brain O2Hb and totHb had increased (P < 0.05) 40.1 ± 18.7 and 26.8 ± 13.6%, respectively. The training intervention shifted breakpoints in muscle HHb, totHb and TOI, and brain O2Hb, HHb, totHb and TOI to a higher absolute work rate and V . ⁢ O 2 (P < 0.05). The relative (in %) change in V . ⁢ O 2 peak was significantly correlated to relative (in %) change slope of muscle TOI (r = 0.69, P = 0.011) and amplitude of muscle HHb (r = 0.72, P = 0.003) and totHb (r = 0.52, P = 0.021), but not to changes in brain oxygenation. These results indicate that interval training affects both muscle and brain oxygenation, coinciding with an increase in aerobic fitness (i.e., V . ⁢ O 2 peak). The relation between the change in V . ⁢ O 2 peak and muscle but not brain oxygenation suggests that brain oxygenation per se is not a primary factor limiting exercise tolerance during incremental exercise.

The Reconstitution of W' Depends on Both Work and Recovery Characteristics.

PURPOSE: This study aimed to investigate the effects of different work and recovery characteristics on the W' reconstitution and to test the predictive capabilities of the W'BAL model. METHODS: Eleven male participants (22 ± 3 yr, 55 ± 4 mL·kg⋅min) completed three to five constant work rate tests to determine CP and W'. Subsequently, subjects performed 12 experimental trials, each comprising two exhaustive constant work rate bouts (i.e., WB1 and WB2), interspersed by an active recovery interval. In each trial, work bout characteristics (P4 or P8, i.e., the work rate predicted to result in exhaustion in 4 and 8 min, respectively), recovery work rate (33% CP or 66% CP), and recovery duration (2, 4, or 6 min) were varied. Actual (W'ACT) and model-predicted (W'PRED) reconstitution values of W' were calculated. RESULTS: After 2, 4, and 6 min recovery, W'ACT averaged 46% ± 2.7%, 51.2% ± 3.3%, and 59.4% ± 4.1%, respectively (P = 0.003). W'ACT was 9.4% higher after recovery at 33% CP than at 66% CP (56.9% ± 3.9% vs 47.5% ± 3.2%) (P = 0.019). P4 exercise yielded a 11.3% higher W'ACT than P8 exercise (57.8% ± 3.9% vs 46.5% ± 2.7%) (P = 0.001). W'ACT was higher than W'PRED in the conditions P4-2 min (+29.7%), P4-4 min (+18.4%), and P8-2 min (+18%) (P < 0.01). A strong correlation (R = 0.68) between the rate of W' depletion and W' recovery was found (P = 0.001). CONCLUSION: This study demonstrated that both the work and recovery characteristics of a prior exhaustive exercise bout can affect the W' reconstitution. Results revealed a slower W' reconstitution when the rate of W' depletion was slower as well. Furthermore, it was shown that the current W'BAL model underestimates actual W' reconstitution, especially after shorter recovery.

Exercise Thresholds on Trial: Are They Really Equivalent?

PURPOSE: The interchangeable use of whole-body exercise thresholds and breakpoints (BP) in the local oxygenation response, as measured via near-infrared spectroscopy, has recently been questioned in scientific literature. Therefore, the present study aimed to longitudinally investigate the interrelationship of four commonly used exercise thresholds: critical power (CP), the respiratory compensation point (RCP), and BP in muscle (m[HHb]BP) and brain (c[O2Hb]BP) oxygenation. METHODS: Nine male participants (21.8 ± 1.2 yr) completed 6 wk of cycling interval training. Before and after this intervention period, subjects performed a ramp incremental exercise protocol to determine RCP, m[HHb]BP, and c[O2Hb]BP and four constant work rate (WR) tests to calculate CP. RESULTS: WR associated with CP, RCP, m[HHB]BP, and c[O2Hb]BP increased by 7.7% ± 4.2%, 13.6% ± 9.0%, 9.8% ± 5.7%, and 11.3% ± 11.1%, respectively. CP was lower (pre: 260 ± 32 W, post: 280 ± 41 W; P < 0.05) than the WR associated with RCP (pre: 281 ± 28 W, post: 318 ± 36 W) and c[O2Hb]BP (pre: 283 ± 36 W, post: 313 ± 32 W) which occurred concomitantly (P = 0.683). M[HHb]BP occurred at the highest WR and differed from all others (pre: 313 ± 23 W, post: 344 ± 32 W; P < 0.05). Training-induced WR differences (ΔWR) did not contrast between thresholds, and initial parameter differences were not affected by the intervention (P = 0.253). Thresholds were partly correlated before (R = 0.67-0.85, P < 0.05) and after (R = 0.83-0.96, P < 0.05) training, but ΔWR values were not associated (P > 0.05). CONCLUSIONS: Results of the present study strongly question true equivalence of CP, RCP, m[HHb]BP, and c[O2Hb]BP during ramp incremental exercise. Therefore, these exercise thresholds should not be used interchangeably.