High-Intensity Interval Training and Sprint-Interval Training in National-Level Rowers

Purpose: The effects of two different high-intensity training methods on 2,000 m rowing ergometer performance were examined in a feasibility study of 24 national-level rowers aged 18–27 years (17 males, 2,000 m ergometer time trial 6:21.7 ± 0:14.6 (min:s) and seven females, 2,000 m ergometer 7:20.3 ± 0:12.1. Habitual training for all participants was ~12–16 h per week).Methods: 16 high-intensity ergometer sessions were completed across two 3-week periods. Participants were allocated into two groups according to baseline 2,000 m time. High-intensity interval session-sprint-interval session (HIIT-SIT) completed eight HIIT (8 × 2.5 min intervals; 95% of 2,000 m wattage) followed by eight SIT (three sets of 7 × 30 s intervals; maximum effort). SIT-HIIT completed eight SIT sessions followed by eight HIIT sessions. Both a 2,000-m time trial and a progressive incremental test finishing with 4 min “all-out” performance were completed before and after each 3-week phase.Results: Both groups showed similar improvements in 2,000 m time and 4 min “all-out” distance after the first 3 weeks (2,000 m time: HIIT-SIT: −2.0 ± 0.6%, mean ± 90% CL, p = 0.01; SIT-HIIT: −1.5 ± 0.3%, p = 0.01) with no significant difference between groups. HIIT-SIT demonstrated the greatest improvements in submaximal heart rate (HR) during the progressive incremental test with eight sessions of HIIT showing a greater reduction in submaximal HR than eight sessions of SIT. The net improvement of 16 high-intensity sessions on 2,000 m time was −2.5% for HIIT-SIT (−10.6 ± 3.9 s, p = 0.01) and − 2.2% for SIT-HIIT (−9.0 ± 5.7 s, p = 0.01) and for 4 min “all-out” performance was 3.1% for HIIT-SIT (36 ± 25 m, p = 0.01) and 2.8% for SIT-HIIT (33 ± 27 m, p = 0.01).Conclusion: Eight sessions of high-intensity training can improve 2,000 m ergometer rowing performance in national-level rowers, with a further eight sessions producing minimal additional improvement. The method of high-intensity training appears less important than the dose.

The Association of Fatigue With Decreasing Regularity of Locomotion During an Incremental Test in Trained and Untrained Healthy Adults

Fatigue is a key factor that affects human motion and modulates physiology, biochemistry, and performance. Prolonged cyclic human movements (locomotion primarily) are characterized by a regular pattern, and this extended activity can induce fatigue. However, the relationship between fatigue and regularity has not yet been extensively studied. Wearable sensor methodologies can be used to monitor regularity during standardized treadmill tests (e.g., the widely used Bruce test) and to verify the effects of fatigue on locomotion regularity. Our study on 50 healthy adults [27 males and 23 females; <40 years; five dropouts; and 22 trained (T) and 23 untrained (U) subjects] showed how locomotion regularity follows a parabolic profile during the incremental test, without exception. At the beginning of the trial, increased walking speed in the absence of fatigue is associated with increased regularity (regularity index, RI, a. u., null/unity value for aperiodic/periodic patterns) up until a peak value (RI = 0.909 after 13.8 min for T and RI = 0.915 after 13.4 min for U subjects; median values, n. s.) and which is then generally followed (after 2.8 and 2.5 min, respectively, for T/U, n. s.) by the walk-to-run transition (at 12.1 min for both T and U, n. s.). Regularity then decreases with increased speed/slope/fatigue. The effect of being trained was associated with significantly higher initial regularity [0.845 (T) vs 0.810 (U), p < 0.05 corrected], longer test endurance [23.0 min (T) vs 18.6 min (U)], and prolonged decay of locomotor regularity [8.6 min (T) vs 6.5 min (U)]. In conclusion, the monitoring of locomotion regularity can be applied to the Bruce test, resulting in a consistent time profile. There is evidence of a progressive decrease in regularity following the walk-to-run transition, and these features unveil significant differences among healthy trained and untrained adult subjects.

Analysis and relationship between the anthropometric and somatotype characteristics and cardiovascular capacity in amateur mountain runners: a pilot study

Purpose: The aim of this study was to describe the anthropometrical and cardiovascular characteristics of short course trail runners and analyze the associations, if any, between both anthropometric and cardiovascular features of amateur trail runners. Material and method: Anthropometrical evaluation and an incremental maximum test with 10% of grade on a treadmill were performed on a group of 10 short distance amateur trail runners. Results: Significant negative correlations were found between the body max index (BMI) and the speed at VT1 (Vel VT1) (r = -0,95, p < 0,001), or the time to reach VT1 (r = -0,91, p = 0,002) and between the body fat percentage and the respiratory exchange ratio at VT2 (r = -0,80, p = 0,016) or the time to reach VT2 (r = -0,83, p = 0,01). Calf circumference was also found to be positively associated with oxygen consumption at VT1 (r = 0,74, p = 0,037), at VT2 (r = 0,90, p = 0,002) and with the maximal oxygen uptake (r = 0,85, p = 0,007). Conclusions: Results indicate that both body fat percentage and calf circumference could be related to the performance on an incremental test protocol with inclination in amateur trail runners.

Concurrent Validity of Power From Three On-Water Rowing Instrumentation Systems and a Concept2 Ergometer

Purpose: Instrumentation systems are increasingly used in rowing to measure training intensity and performance but have not been validated for measures of power. In this study, the concurrent validity of Peach PowerLine (six units), Nielsen-Kellerman EmPower (five units), Weba OarPowerMeter (three units), Concept2 model D ergometer (one unit), and a custom-built reference instrumentation system (Reference System; one unit) were investigated.Methods: Eight female and seven male rowers [age, 21 ± 2.5 years; rowing experience, 7.1 ± 2.6 years, mean ± standard deviation (SD)] performed a 30-s maximal test and a 7 × 4-min incremental test once per week for 5 weeks. Power per stroke was extracted concurrently from the Reference System (via chain force and velocity), the Concept2 itself, Weba (oar shaft-based), and either Peach or EmPower (oarlock-based). Differences from the Reference System in the mean (representing potential error) and the stroke-to-stroke variability (represented by its SD) of power per stroke for each stage and device, and between-unit differences, were estimated using general linear mixed modeling and interpreted using rejection of non-substantial and substantial hypotheses.Results: Potential error in mean power was decisively substantial for all devices (Concept2, –11 to –15%; Peach, −7.9 to −17%; EmPower, −32 to −48%; and Weba, −7.9 to −16%). Between-unit differences (as SD) in mean power lacked statistical precision but were substantial and consistent across stages (Peach, ∼5%; EmPower, ∼7%; and Weba, ∼2%). Most differences from the Reference System in stroke-to-stroke variability of power were possibly or likely trivial or small for Peach (−3.0 to −16%), and likely or decisively substantial for EmPower (9.7–57%), and mostly decisively substantial for Weba (61–139%) and the Concept2 (−28 to 177%).Conclusion: Potential negative error in mean power was evident for all devices and units, particularly EmPower. Stroke-to-stroke variation in power showed a lack of measurement sensitivity (apparent smoothing) that was minor for Peach but larger for the Concept2, whereas EmPower and Weba added random error. Peach is therefore recommended for measurement of mean and stroke power.

Functional Threshold Power Estimated from a 20-minute Time-trial Test is Warm-up-dependent

This study investigated the influence of different warm-up protocols on functional threshold power. Twenty-one trained cyclists (˙VO2max=60.2±6.8 ml·kg−1·min−1) performed an incremental test and four 20-min time trials preceded by different warm-up protocols. Two warm-up protocols lasted 45 min, with a 5-min time trial performed either 15 min (Traditional) or 25 min (Reverse) before the 20-min time trial. The other two warm-up protocols lasted 25 min (High Revolutions-per minute) and 10 min (Self-selected), including three fast accelerations and self-selected intensity, respectively. The power outputs achieved during the 20-min time trial preceded by the Traditional and Reverse warm-up protocols were significantly lower than the High Revolutions-per-minute and Self-selected protocols (256±30; 257±30; 270±30; 270±30 W, respectively). Participants chose a conservative pacing strategy at the onset (negative) for the Traditional and Reverse but implemented a fast-start strategy (U-shaped) for the High revolutions-per-minute and Self-selected warm-up protocols. In conclusion, 20-min time-trial performance and pacing are affected by different warm-ups. Consequently, the resultant functional threshold power may be different depending on whether the original protocol with a 5-min time trial is followed or not.

Real Assessment of Maximum Oxygen Uptake as a Verification After an Incremental Test Versus Without a Test

The study was conducted to compare peak oxygen uptake (VO2peak) measured with the incremental graded test (GXT) (VO2peak) and two tests to verify maximum oxygen uptake, performed 15 min after the incremental test (VO2peak1) and on a separate day (VO2peak2). The aim was to determine which of the verification tests is more accurate and, more generally, to validate the VO2max obtained in the incremental graded test on cycle ergometer. The study involved 23 participants with varying levels of physical activity. Analysis of variance showed no statistically significant differences for repeated measurements (F = 2.28, p = 0.118, η2 = 0.12). Bland–Altman analysis revealed a small bias of the VO2peak1 results compared to the VO2peak (0.4 ml⋅min–1⋅kg–1) and VO2peak2 results compared to the VO2peak (−0.76 ml⋅min–1⋅kg–1). In isolated cases, it was observed that VO2peak1 and VO2peak2 differed by more than 5% from VO2peak. Considering the above, it can be stated that among young people, there are no statistically significant differences between the values of VO2peak measured in the following tests. However, in individual cases, the need to verify the maximum oxygen uptake is stated, but performing a second verification test on a separate day has no additional benefit.

Sex-Differences in the Oxygenation Levels of Intercostal and Vastus Lateralis Muscles During Incremental Exercise

This study aimed to examine sex differences in oxygen saturation in respiratory (SmO2-m.intercostales) and locomotor muscles (SmO2-m.vastus lateralis) while performing physical exercise. Twenty-five (12 women) healthy and physically active participants were evaluated during an incremental test with a cycle ergometer, while ventilatory variables [lung ventilation (V.E), tidal volume (Vt), and respiratory rate (RR)] were acquired through the breath-by-breath method. SmO2 was acquired using the MOXY® devices on the m.intercostales and m.vastus lateralis. A two-way ANOVA (sex × time) indicated that women showed a greater significant decrease of SmO2-m.intercostales, and men showed a greater significant decrease of SmO2-m.vastus lateralis. Additionally, women reached a higher level of ΔSmO2-m.intercostales normalized to V.E (L⋅min–1) (p &lt; 0.001), whereas men had a higher level of ΔSmO2-m.vastus lateralis normalized to peak workload-to-weight (watts⋅kg–1, PtW) (p = 0.049), as confirmed by Student’s t-test. During an incremental physical exercise, women experienced a greater cost of breathing, reflected by greater deoxygenation of the respiratory muscles, whereas men had a higher peripheral load, indicated by greater deoxygenation of the locomotor muscles.

Acute melatonin administration improves exercise tolerance and the metabolic recovery after exhaustive effort

The present study investigated the effects of acute melatonin administration on the biomarkers of energy substrates, GLUT4, and FAT/CD36 of skeletal muscle and its performance in rats subjected to exhaustive swimming exercise at an intensity corresponding to the maximal aerobic capacity (tlim). The incremental test was performed to individually determine the exercise intensity prescription and 48 h after, the animals received melatonin (10 mg·kg−1) or vehicles 30 min prior to tlim. Afterwards, the animals were euthanized 1 or 3 h after the exhaustion for blood and muscles storage. The experiment 1 found that melatonin increased the content of glycogen and GLUT4 in skeletal muscles of the animals that were euthanized 1 (p < 0.05; 22.33% and 41.87%) and 3 h (p < 0.05; 37.62% and 57.87%) after the last procedures. In experiment 2, melatonin enhanced the tlim (p = 0.01; 49.42%), the glycogen content (p < 0.05; 40.03%), GLUT4 and FAT/CD36 in exercised skeletal muscles (F = 26.83 and F = 25.28, p < 0.01). In summary, melatonin increased energy substrate availability prior to exercise, improved the exercise tolerance, and accelerated the recovery of muscle energy substrates after the tlim, possibly through GLUT4 and FAT/CD36.

Effect of Different Types of Face Masks on the Ventilatory and Cardiovascular Response to Maximal-Intensity Exercise

The development of new models of face masks makes it necessary to compare their impact on exercise. Therefore, the aim of this work was to compare the cardiopulmonary response to a maximal incremental test, perceived ventilation, exertion, and comfort using FFP2 or Emotion masks in young female athletes. Thirteen healthy sportswomen (22.08 ± 1.75 years) performed a spirometry, and a graded exercise test on a treadmill, with a JAEGER® Vyntus CPX gas analyzer using an ergospirometry mask (ErgoMask) or wearing the FFP2 or the Emotion mask below the ErgoMask, randomized on 3 consecutive days. Also, menstrual cycle status was monitored to avoid possible intrasubject alterations. The results showed lower values for the ErgoMask+FFP2, compared to ErgoMask or ErgoMask+Emotion, in forced vital capacity (3.8 ± 0.2, 4.5 ± 0.2 and 4.1 ± 0.1 l, respectively); forced expiratory volume in 1 s (3.3 ± 0.2, 3.7 ± 0.2 and 3.5 ± 0.1 l); ventilation (40.9 ± 1.5, 50.6 ± 1.5 and 46.9 ± 1.2 l/min); breathing frequency (32.7 ± 1.1, 37.4 ± 1.1 and 35.3 ± 1.4 bpm); VE/VO2 (30.5 ± 0.7, 34.6 ± 0.9 and 33.6 ± 0.7); VE/VCO2 (32.2 ± 0.6, 36.2 ± 0.9 and 34.4 ± 0.7) and time to exhaustion (492.4 ± 9.7, 521.7 ± 8.6 and 520.1 ± 9.5 s) and higher values in inspiratory time (0.99 ± 0.04, 0.82 ± 0.03 and 0.88 ± 0.03 s).. In conclusion, in young healthy female athletes, the Emotion showed better preservation of cardiopulmonary responses than the FFP2.

The influence of calculation method and relative strength on the load-velocity relationship in bench press exercise

Purpose The objective of this study was: (1) to compare the effect of the calculation method using average (Avalue), and best value (Bvalue) of Mean Propulsive Velocity (MPV) on the Load Velocity Profile (LVprofile) during the barbell bench press exercise in elite handball players. In addition, (2) to analyze the relationship between the individual coefficient of variation (CVind) of an incremental load protocol in the bench press exercise with relative strength (Frel) in professional handball players. Methods Nineteen elite international handball players (age 18 [±1] y; body mass 93 [±14] kg; height 191 [±6] cm) performed an incremental test during the barbell bench press exercise. General and individual LVprofile, Frel, and CVind were modelled through MPV and two calculation models (Avalue, vs Bvalue). Results There were significant differences (p < 0.05) between both conditions (Bvalue vs. Avalue). There was an inverse relationship between the Frel and the CVind (r = −0.66, p < 0.001). When CVind was >10% significant differences were found between the two calculations method (Avalue, vs Bvalue). However, no significant differences were found between Avalue, vs Bvalue when the CVind was <10%. Conclusions The calculation method used to assess the barbell bench press LVprofile impacts the nature of the relationship. Regardless CVind values, Avalue is a good choice to determine the LVprofile when the CVind is >10%, if the CVind is <10%, Bvalue will be the better option to determine the LVprofile.