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Adaptations to aerobic interval training: Interactive effects of exercise intensity and total work duration
Abstract
To compare the effects of three 7-week interval training programs varying in work period duration but matched for effort in trained recreational cyclists. Thirty-five cyclists (29 male, 6 female, VO(2peak) 52 ± 6 mL kg/min) were randomized to four training groups with equivalent training the previous 2 months (∼6 h/wk, ∼1.5 int. session/wk). Low only (n=8) trained 4-6 sessions/wk at a low-intensity. Three groups (n=9 each) trained 2 sessions/wk × 7 wk: 4 × 4 min, 4 × 8 min, or 4 × 16 min, plus 2-3 weekly low-intensity bouts. Interval sessions were prescribed at the maximal tolerable intensity. Interval training was performed at 88 ± 2, 90 ± 2, and 94 ± 2% of HR(peak) and 4.9, 9.6, and 13.2 mmol/L blood lactate in 4 × 16, 4 × 8, and 4 × 4 min groups, respectively (both P<0.001). 4 × 8min training induced greater overall gains in VO(2) peak, power@VO(2) peak, and power@4 mM bLa- (Mean ± 95%CI): 11.4 (8.0-14.9), vs 4.2 (0.4-8.0), 5.6 (2.1-9.1), and 5.5% (2.0-9.0) in Low, 4 × 16, and 4 × 4 min groups, respectively (P<0.02 for 4 × 8 min vs all other groups). Interval training intensity and accumulated duration interact to influence the adaptive response. Accumulating 32 min of work at 90% HR max induces greater adaptive gains than accumulating 16 min of work at ∼95% HR max despite lower RPE.
... Aerobic intervals are performed with submaximal effort, while anaerobic intervals are performed at maximum effort and last up to 75 s (Gastin, 2001). Aerobic intervals are further categorized into traditional long intervals with durations of 2-10 min (Seiler et al., 2013;Spencer et al., 1996;Sandbakk et al., 2013) and intermittent short intervals with durations of 15-60 s (Helgerud et al., 2007;Stöggl et al., 2023). For anaerobic intervals, we included an intermediate level: speed endurance training (SET) and sprint interval training (SIT). ...
... Although we found little evidence of publication bias across all the measures, our method for detecting and eliminating such bias may not be trustworthy if statistical significance was required for the publication of most of the study estimates. We, therefore, performed worst-case scenario simulations with the mean sample size (Seiler et al., 2013) and error of measurement (3.1%) for the HIIT group in theVO 2max studies to determine the published mean effect for different true mean effects when only significant effects are published. A true effect of 10% would result in negligible upward publication bias, and substantial bias becomes evident only for true effects of 5% (published mean effect 6%) [HPW and WGH (Wiesinger et al., 2024a)]. ...
Introduction
Meta-analysts have found that high-intensity interval training (HIIT) improves physical performance, but limited evidence exists regarding its effects on highly trained athletes, measures beyond maximum oxygen uptake ( V ˙ O2max), and the moderating effects of different types of HIIT. In this study, we present meta-analyses of the effects of HIIT focusing on these deficits.
Methods
The effects of 6 types of HIIT and other moderators were derived from 34 studies involving highly trained endurance and elite athletes in percent units via log-transformation from separate meta-regression mixed models for sprint, time–trial, aerobic/anaerobic threshold, peak speed/power, repeated-sprint ability, V ˙ O2max, and exercise economy. The level of evidence for effect magnitudes was evaluated based on the effect uncertainty and the smallest important change of 1%.
Results
Compared with control training, HIIT showed good to excellent evidence for the substantial enhancement of most measures for some athlete subgroups in practically important study settings defined by effect moderators (maximum of 12.6%, for endurance female athletes after 6 weeks of aerobic traditional long intervals). The assessment of the moderators indicated good evidence of greater effects as follows: with more aerobic types of HIIT for V ˙ O2max (+2.6%); with HIIT added to conventional training for most measures (+1.1–2.3%); during the competition phase for V ˙ O2max (+4.3%); and with tests of longer duration for sprint (+5.5%) and time trial (+4.9%). The effects of sex and type of athlete were unclear moderators. The heterogeneity of HIIT effects within a given type of setting varied from small to moderate (standard deviations of 1.1%–2.3%) and reduced the evidence of benefit in some settings.
Conclusion
Although athletes in some settings can be confident of the beneficial effects of HIIT on some measures related to competition performance, further research is needed. There is uncertainty regarding the mean effects on exercise economy and the modifying effects of sex, duration of intervention, phase of training, and type of HIIT for most measures.
Systematic Review Registration
https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=236384.
... Although no standardized criteria currently exist for defning these training zones [6], each zone is often determined by objective physiological markers, such as heart rate and blood lactate concentration [17][18][19][20][21][22][23][24][25][26][27][28] and ventilatory response [9,[29][30][31][32], or by power output or velocity [24,[33][34][35][36][37][38][39][40]. Based on the athlete's specifc needs and objectives, this zonal approach enables the individualized tailoring of training stimuli to elicit targeted metabolic and performance outcomes, such as enhancing aerobic capacity, optimizing fuel utilization [41], or improving lactate clearance efciency [2,42,43]. ...
Introduction: Endurance athletes often utilize low-intensity training, commonly defined as Zone 2 (Z2) within a five-zone intensity model, for its potential to enhance aerobic adaptations and metabolic efficiency. This study aimed at evaluating intra- and interindividual variability of commonly used Z2 intensity markers to assess their precision in reflecting physiological responses during training.
Methods: Fifty cyclists (30 males and 20 females) performed both an incremental ramp and a step test in a laboratory setting, during which the power output, heart rate, blood lactate, ventilation, and substrate utilization were measured.
Results: Analysis revealed substantial variability in Z2 markers, with the coefficients of variation (CV) ranging from 6% to 29% across different parameters. Ventilatory Threshold 1 (VT1) and maximal fat oxidation (FatMax) showed strong alignment, whereas fixed percentages of HRmax and blood lactate thresholds exhibited wide individual differences.
Discussion: Standardized markers for Z2, such as fixed percentages of HRmax, offer practical simplicity but may inaccurately reflect metabolic responses, potentially affecting training outcomes. Given the considerable individual variability, particularly in markers with high CVs, personalized Z2 prescriptions based on physiological measurements such as VT1 and FatMax may provide a more accurate approach for aligning training intensities with metabolic demands. This variability highlights the need for individualized low-intensity training prescriptions to optimize endurance adaptations in cyclists, accommodating differences in physiological profiles and improving training specificity.
... The study found no significant changes in body weight, BMI, or metabolic age after the two-month training period (p>0.05). These results are consistent with previous research suggesting that well-trained athletes, especially those in endurance sports like cycling, may not exhibit noticeable changes in these parameters after short-term training [5,15] . ...
This study aimed to evaluate the effects of a two-month intensive physical training program on the physiological and physical profiles of elite Cameroonian cyclists. A total of 10 cyclists were assessed on a range of parameters before and after the training program, including anthropometric, body composition, hemodynamic, and physical performance measures. Anthropometric parameters (height, body weight, body mass index, and metabolic age) showed no significant changes (p > 0.05). In contrast, body composition analysis revealed a significant reduction in body fat percentage (22.27%) and an increase in muscle mass (4.70%, p < 0.05), with no significant changes in body water percentage (p > 0.05). Hemodynamic assessments demonstrated a significant decrease in systolic blood pressure (6.41%) (p < 0.05), while resting heart rate and diastolic blood pressure remained unchanged (p > 0.05). In terms of physical performance, vertical jump height, leg strength, and arm strength showed significant improvements, with increases of 7.70%, 17.95%, and 16.01%, respectively (p < 0.05 to p < 0.001). Sprint performance improved by 3.10%, but no significant changes were found in grip strength and VO₂ max (p > 0.05). These findings suggest that short-term intensive training programs can significantly improve certain aspects of body composition and physical performance, while having minimal impact on anthropometric and cardiovascular parameters in elite cyclists.
... V. Billat et al. 1996). According to these definitions, the size of the over or underestimation would dictate the suitability of the testing procedure to prescribe the HIIT, which aims to accumulate the maximal time over 90% ofVO 2 max (Buchheit et al. 2013;Seiler et al. 2013). ...
This study aims to determine the validity of the linear critical power (CP) and Peronnet models to estimate the power output associated with the second ventilatory threshold (VT2) and the maximal aerobic power (MAP) using two‐time trials. Nineteen recreational runners (10 males and 9 females and maximum oxygen uptake: 53.0 ± 4.7 mL/kg/min) performed a graded exercise test (GXT) to determine the VT2 and MAP. On a second test, athletes performed two‐time trials of 9 and 3 min interspaced by 30 min. The CP was determined from the linear CP model and compared with the power output associated with the VT2. The MAP was determined from the linear Peronnet model, established at 7 min, and compared with the MAP determined in the GXT. The CP model was valid for determining the VT2, regardless of sex (p = 0.130; 9/3 vs. GXT: 3.5 [−1.1 to 8.2] W). The MAP was overestimated (p = 0.015) specifically in males (9/3 vs. GXT: 9.2 [3.3 to 15.1] W) rather than in females (p = 9/3 vs. GXT: 1.7 [−4.4 to 8.0] W). Therefore, MAP estimates were determined introducing the CP and W' parameters to a stepwise multiple linear regression analysis. For females, the CP was the unique significant predictor of MAP (p < 0.001) explaining 96.7% of the variance. In males, both CP and W' were significant predictors of MAP (p < 0.001) explaining 97.7% of the variance. Practitioners can validly estimate the VT2 and MAP through a practical testing protocol in both male and female recreational runners.
... Practically, as exercise intensities around LT2 are commonly used to prescribe interval training sessions, using hypoxia to lessen the mechanical load may not be suitable for all interval training sessions. For example, work durations at LT2 have been previously described as 4 � 4 min, 4 � 8 min and 4 � 16 min, representing short, medium and long intervals, respectively (Seiler et al., 2013). In this context, only long intervals would exhibit a decrease in the mechanical load due to hypoxia exposure, whereas no difference in cycling PO would be observed during medium and short intervals. ...
The effects of acute hypoxic exposure on mechanical output and internal responses during cycling with heart rate (HR) clamped at lactate thresholds 1 and 2 (LT1 and LT2, respectively) were investigated. On separate days, 12 trained males cycled for 15 min at a clamped HR corresponding to LT1 and LT2 under normoxic or hypoxic conditions (simulated altitude of ∼3500 m and inspired oxygen fraction of 13.6%). Power output (PO), arterial oxygen saturation, ventilatory and perceptual responses were measured every 3 min, with metabolic response assessed pre‐ and post‐exercise. At LT1, PO was consistently lower in hypoxia compared to normoxia (p < 0.01). At LT2, PO was not different between normoxia and hypoxia at 3 and 6 min (both p > 0.42) but was significantly lower in hypoxia at 9, 12 and 15 min (all p < 0.04). Overall, hypoxia induced a greater decrease in PO at LT1 (−33.3% ± 11.3%) than at LT2 (−18.0 ± 14.7%) compared to normoxia. Ventilatory, perceptual and metabolic responses were influenced by exercise intensity (all p < 0.01) but not environmental conditions (all p > 0.17). A simulated altitude of ∼3500 m is more effective in reducing cycling PO at LT1 than LT2 during HR clamped cycling while maintaining other internal loads. Therefore, normobaric hypoxia provides a greater benefit via a larger decrease in the mechanical constraints of exercise at lower exercise intensities.
... One of the workouts is a longer endurance-based workout of about 30-40 min of intermittent exercise at around 90% of vVo2max (race pace of about 10 km for elite racers), with a load/rest ratio of about 1:3 or 1:2. Seiler often recommends this type of training with 8 3 4 min with 2 min rests, then progressing this training to 4 3 8 min with 2 min rests at the same intensity as the season progresses [39]. The other intense training primarily uses short intervals (>60 s) at vVo2max or faster. ...
This study aims to present the significant training theoretical innovations in the history of modern distance running that can be traced back to the countries of Northern Europe and the possible underlying socio-historical reasons for them. Since the beginning of the modern sport, the Nordic countries have enjoyed outstanding success in distance running. In the 1910s-20s, the dominance of Finnish runners was a feature of the first year-round systematic training. During the Second World War, the Swedish coach Gosta Holmer developed the fartlek (speed play) method, which enabled his runners to set numerous world records between 1,500 m and 10,000 m. The most significant innovation in modern distance running training methods was the scientifically based interval training of the German Dr Woldemar Gerschler, which still determines athletes' training today. The Dutchman Herman Verheul developed his easy interval method based on the empirical observations of the Gerchler system. The Verheul method was characterized by high-volume and mainly aerobic sub-maximal speeds and a big emphasis on aerobic development. This is the basis of the Norwegian training method that dominates sports science research today. The latter uses longer intervals (1,000-2,000 m) developing anaerobic-threshold speed (vLT2) monitored by lactate measurement several times a week. These innovations have been fostered by various sociological facts (promotion of sports, sports sciences, and use of the results) and the historical context of the era.
Purpose
High-intensity functional interval training (HIFT) is predominantly composed of high exercise training intensities (HiT) and loads. Both have been linked to a higher risk of overtraining and injuries in inexperienced populations. A polarized training approach is characterized by high amounts of low-intensity training (LiT) and only approximately 5%–20% HiT. Compared to HIT-based training, this approach can result in temporary training load and intensity reductions without diminishing training gains. Thus, we aimed to examine the effects of traditional (TRAD) HIFT vs. polarized (POL) HIFT on relevant performance parameters.
Methods
Thirty athletes (15 females, age: 26.6 ± 5.0 years, height: 1.76 ± 0.13 m, body mass: 79.6 ± 12.4 kg, prior experience: 2.3 ± 2.0 years, training volume: 6.1 ± 2.4 h/wk) were randomly assigned to 6 weeks of either POL (78% LiT, 22% threshold intensity training (ThT) to HiT) or TRAD (26% LiT, 74% ThT to HiT). HIFT performance testing focused on maximal strength (squat: SQ1RM, deadlift: DL1RM, overhead press: OHP1RM, high pull: HP1RM), endurance (peak oxygen uptake: V̇O2peak, lactate threshold: LT, peak power output (PPO), and benchmark HIFT workout (Jackie: 1000 m rowing, 50 thrusters, and 30 pull-ups for time).
Results
POL (785 ± 71 au) completed significantly (p ≤ 0.001; SMD = 4.55) lower training load (eTRIMP) than TRAD (1,273 ± 126 au). rANCOVA revealed no statistical relevant group×time interaction effects (0.094 ≤ p ≤ 0.986; 0.00 ≤ ηp ² ≤ 0.09) for SQ1RM, DL1RM, OHP1RM, high pull, V̇O2peak, LT, PPO, and Jackie performance. Both groups revealed trivial to moderate but significant (rANCOVA time effects: p ≤ 0.02; 0.01 ≤ ηp ² ≤ 0.11; 0.00 ≤ SMD ≤ 0.65) performance gains regarding DL1RM, OHP1RM, HP1RM, and Jackie.
Conclusion
Despite a notably lower total training load, conditioning gains were not affected by a polarized functional interval training regimen.
Objectives. — During interval training, the combination of several training components (stimulus duration, intensity, and recovery) determines the athlete’s acute fatigue, and manipulating these components elicits different acute fatigue responses. We analyzed the effects of manipulating the duration of the recovery period during isoeffort interval training sessions on biomechanical, physiological, perceptual, and neuromuscular parameters.
Equipment and methods. — Twelve well-trained runners completed three interval sessions at the highest possible running speed (4 × 4 min) on a treadmill with 1-min, 2-min, or self-selected (SSrecovery) passive recovery periods (standing quietly on the treadmill).
Results. — Overall speed and distance after 4 × 4 min were 2.5% higher with a SSrecovery (∼190s) when they were compared to 1-min (P < 0.05) and 2-min recoveries (P < 0.05). Blood lactate concentration (P < 0.05) was 15.6% lower in SSrecovery when compared to 1-min recovery. Rating of perceived exertion was 6.7% higher in 1-min vs. 2-min and SSrecovery (P < 0.05). Vertical oscillation was 3.4% lower in SSrecovery vs. 1-min (P < 0.05), and step frequency was also 1.3 and 1.4% lower in 1-min and 2-min recovery periods when compared to SSrecovery (P < 0.01; P < 0.05).
Conclusions. — These results suggest that self-selected recovery with a mean duration of 190 s involves less fatigue than 1- or 2-min recoveries after 3 long interval training sessions (4 × 4 min). In fact, self-selected recovery showed lower blood lactate concentration, vertical oscillation, RPE and step frequency than 1- or 2-min recovery.
Purpose : To compare designs of training sessions applied by world-class cross-country skiers during their most successful junior and senior season. Methods : Retrospective analysis of self-reported training characteristics (ie, training form, intensity, and exercise mode) among 8 male and 7 female world-class cross-country skiers was conducted. Results : Total number of sessions (441 [71] vs 519 [34], P < .001, large effect) and mean duration (1.5 [0.1] h vs 1.7 [0.1] h, P < .001, moderate effect) increased from junior to senior age. More double-session days were performed at senior age (124 [50] vs 197 [29] d, P < .001, large). The number (310 [64] vs 393 [64], P < .001, large effect) and duration (1.3 [0.1] h vs 1.5 [0.1] h, P < .001, moderate effect) of low-intensity training sessions increased from junior to senior age. Regarding intensive training, most emphasis was put on high-intensity training sessions lasting 20 to 39 minutes with <5-minute intervals at junior age, while 40 to 59 minutes of moderate-intensity training with 5- to 9-minute intervals was predominant at senior age. More MIXED (combined moderate- and high-intensity) sessions (9 [7] vs 14 [7], P = .023, moderate effect) and longer races (0.5 [0.1] h vs 0.6 [0.1] h, P = 0.29, moderate effect) compensated for fewer high-intensity training sessions at senior age (36 [17] vs 25 [10], P = .027, moderate effect). Duration of strength-training sessions increased significantly (0.6 [0.1] vs 0.8 [0.2] h, P = 0.30, moderate effect), while other training forms remained unchanged. Conclusions : World-class cross-country skiers increased their training volume from junior to senior age primarily by more and longer low-intensity training sessions and more often training twice per day. Concurrently, the most frequent intensive sessions were modified from high- to moderate-intensity training, lasted longer, and contained longer intervals.
This study aims to investigate the differences and similarities between the polarized and pyramid-intensity training methods described in the literature as the most typical training methods for elite international distance runners (1500- 10,000 m). Material and Methods: 26 literature articles analyzing the training intensity distribution of international distance runners were found after a review of internet databases. Results: In both training methods, elite track runners cover an average of 120-180 km per week, 75-80% of which is done at low intensity, below the aerobic threshold (vLT1). In the pyramid method, runners perform interval or continuous tempo running workouts at speeds below the anaerobic threshold (vLT2) on average 2-4 times per week. In contrast, in the polarized intensity distribution, interval training is performed on average 1 time per week above the anaerobic threshold at 90% of vVo2max. Intensities near race speed are performed as short intervals (< 800m) during the base period. Conclusions: The training of modern distance runners is characterized by an emphasis on the development of aerobic capacity, achieved primarily through high amounts of low-intensity work and 1-4 anaerobic threshold training sessions per week. Athletes use short intervals and short sprints to maintain their anaerobic abilities and their coordination at race speed. They start using longer, intensive race-specific work in the period leading up to races. During the racing season, runners maintain endurance with a significant amount of low-intensity running and less pronounced anaerobic threshold training.
Endurance training involves manipulation of intensity, duration, and frequency of training sessions. The relative impact of short, high-intensity training versus longer, slower distance training has been studied and debated for decades among athletes, coaches, and scientists. Currently, the popularity pendulum has swung towards high-intensity interval training. Many fitness experts, as well as some scientists, now argue that brief, high-intensity interval work is the only form of training necessary for performance optimization. Research on the impact of interval and continuous training with untrained to moderately trained subjects does not support the current interval craze, but the evidence does suggest that short intense training bouts and longer continuous exercise sessions should both be a part of effective endurance training. Elite endurance athletes perform 80 % or more of their training at intensities clearly below their lactate threshold and use high-intensity training surprisingly sparingly. Studies involving intensification of training in already well-trained athletes have shown equivocal results at best. The available evidence suggests that combining large volumes of low-intensity training with careful use of high-intensity interval training throughout the annual training cycle is the best-practice model for development of endurance performance. KEYWORDS: lactate threshold, maximal oxygen uptake, VO2max, periodization.
ACSM Position Stand on The Recommended Quantity and Quality of Exercise for Developing and Maintaining Cardiorespiratory and Muscular Fitness, and Flexibility in Adults. Med. Sci. Sports Exerc., Vol. 30, No. 6, pp. 975-991, 1998. The combination of frequency, intensity, and duration of chronic exercise has been found to be effective for producing a training effect. The interaction of these factors provide the overload stimulus. In general, the lower the stimulus the lower the training effect, and the greater the stimulus the greater the effect. As a result of specificity of training and the need for maintaining muscular strength and endurance, and flexibility of the major muscle groups, a well-rounded training program including aerobic and resistance training, and flexibility exercises is recommended. Although age in itself is not a limiting factor to exercise training, a more gradual approach in applying the prescription at older ages seems prudent. It has also been shown that aerobic endurance training of fewer than 2 d·wk-1, at less than 40-50% of V˙O2R, and for less than 10 min-1 is generally not a sufficient stimulus for developing and maintaining fitness in healthy adults. Even so, many health benefits from physical activity can be achieved at lower intensities of exercise if frequency and duration of training are increased appropriately. In this regard, physical activity can be accumulated through the day in shorter bouts of 10-min durations.
In the interpretation of this position stand, it must be recognized that the recommendations should be used in the context of participant's needs, goals, and initial abilities. In this regard, a sliding scale as to the amount of time allotted and intensity of effort should be carefully gauged for the cardiorespiratory, muscular strength and endurance, and flexibility components of the program. An appropriate warm-up and cool-down period, which would include flexibility exercises, is also recommended. The important factor is to design a program for the individual to provide the proper amount of physical activity to attain maximal benefit at the lowest risk. Emphasis should be placed on factors that result in permanent lifestyle change and encourage a lifetime of physical activity.
Successful endurance training involves the manipulation of training intensity, duration, and frequency, with the implicit goals of maximizing performance, minimizing risk of negative training outcomes, and timing peak fitness and performances to be achieved when they matter most. Numerous descriptive studies of the training characteristics of nationally or internationally competitive endurance athletes training 10 to 13 times per week seem to converge on a typical intensity distribution in which about 80% of training sessions are performed at low intensity (2 mM blood lactate), with about 20% dominated by periods of high-intensity work, such as interval training at approx. 90% VO2max. Endurance athletes appear to self-organize toward a high-volume training approach with careful application of high-intensity training incorporated throughout the training cycle. Training intensification studies performed on already well-trained athletes do not provide any convincing evidence that a greater emphasis on high-intensity interval training in this highly trained athlete population gives long-term performance gains. The predominance of low-intensity, long-duration training, in combination with fewer, highly intensive bouts may be complementary in terms of optimizing adaptive signaling and technical mastery at an acceptable level of stress.
The pattern of energy expenditure during sustained high-intensity exercise is influenced by several variables. Data from athletic populations suggest that a pre-exercise conceptual model, or template, is a central variable relative to controlling energy expenditure.
The aim of this study was to make systematic observations regarding how the performance template develops in fit individuals who have limited specific experience with sustained high-intensity exercise (eg, time trials).
The study was conducted in four parts and involved measuring performance (time and power output) during: (A) six 3 km cycle time trials, (B) three 2 km rowing time trials, (C) four 2 km rowing time trials with a training period between trials 2 and 3, and (D) three 10 km cycle time trials. All time trials were self-paced with feedback to the subjects regarding previous performances and momentary pace.
In all four series of time trials there was a progressive pattern of improved performance averaging 6% over the first three trials and 10% over six trials. In all studies improvement was associated with increased power output during the early and middle portions of the time trial and a progressively greater terminal rating of perceived exertion. Despite the change in the pattern of energy expenditure, the subjects did not achieve the pattern usually displayed by athletes during comparable events.
This study concludes that the pattern of learning the performance template is primarily related to increased confidence that the trial can be completed without unreasonable levels of exertion or injury, but that the process takes more than six trials to be complete.
Performance in intense exercise events, such as Olympic rowing, swimming, kayak, track running and track cycling events, involves energy contribution from aerobic and anaerobic sources. As aerobic energy supply dominates the total energy requirements after ∼75s of near maximal effort, and has the greatest potential for improvement with training, the majority of training for these events is generally aimed at increasing aerobic metabolic capacity. A short-term period (six to eight sessions over 2-4 weeks) of high-intensity interval training (consisting of repeated exercise bouts performed close to or well above the maximal oxygen uptake intensity, interspersed with low-intensity exercise or complete rest) can elicit increases in intense exercise performance of 2-4% in well-trained athletes. The influence of high-volume training is less discussed, but its importance should not be downplayed, as high-volume training also induces important metabolic adaptations. While the metabolic adaptations that occur with high-volume training and high-intensity training show considerable overlap, the molecular events that signal for these adaptations may be different. A polarized approach to training, whereby ∼75% of total training volume is performed at low intensities, and 10-15% is performed at very high intensities, has been suggested as an optimal training intensity distribution for elite athletes who perform intense exercise events.
The purpose of this study was to determine the accuracy of the Velotron cycle ergometer and the SRM power meter using a dynamic calibration rig over a range of exercise protocols commonly applied in laboratory settings. These trials included two sustained constant power trials (250 W and 414 W), two incremental power trials and three high-intensity interval power trials. To further compare the two systems, 15 subjects performed three dynamic 30 km performance time trials. The Velotron and SRM displayed accurate measurements of power during both constant power trials (<1% error). However, during high-intensity interval trials the Velotron and SRM were found to be less accurate (3.0%, CI=1.6-4.5% and -2.6%, CI=-3.2--2.0% error, respectively). During the dynamic 30 km time trials, power measured by the Velotron was 3.7+/-1.9% (CI=2.9-4.8%) greater than that measured by the SRM. In conclusion, the accuracy of the Velotron cycle ergometer and the SRM power meter appears to be dependent on the type of test being performed. Furthermore, as each power monitoring system measures power at various positions (i.e. bottom bracket vs. rear wheel), caution should be taken when comparing power across the two systems, particularly when power is variable.
To investigate the effect of task familiarisation on the spontaneous pattern of energy expenditure during a series of 2000 m cycling time trials (TTs).
Nine trained males completed three 2000 m TTs on a Velotron cycling ergometer. To examine pacing strategy, the data were assigned to 250 m "bins," with the pattern of aerobic and anaerobic energy expenditure calculated from total work accomplished and gas-exchange data.
There were no significant differences between trials in performance times (191.4 (SD 4.3), 189.4 (4.6), 190.1 (5.6) s), total aerobic (58.3 (2.7), 58.4 (3.1), 58.0 (3.4) kJ) and total anaerobic energy expenditure (16.4 (3.3), 17.3 (2.8), 16.5 (3.1) kJ). Pacing strategy in the second and third TT differed from the first TT in that a lower power output was adopted during the first 500 m, enabling a higher power output during the final 750 m of the TT. This adjustment in the pattern of energy expenditure was mediated by an alteration in the pattern of anaerobic energy expenditure, which paralleled changes in total energy expenditure. Furthermore, participants retained an anaerobic energy "reserve" enabling an end-spurt during the second and third trials.
Small modifications to the pacing strategy are made following a single bout of exercise, primarily by altering the rate of anaerobic energy expenditure. This may have served to prevent critical metabolic disturbances. The alteration in pacing strategy following the first exercise bout is compatible with a complex intelligent regulatory system.