‘Priming’ exercise and O2 uptake kinetics during treadmill running

Jones, Andrew M.; DiMenna, Fred J.; Lothian, Fiona; Taylor, Esme; Garland, Stephen; Hayes, Philip R.; Thompson, Kevin G.

doi:10.1016/j.resp.2008.02.001

Cited by 23 publications

(25 citation statements)

References 57 publications

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“…In order to determine the time needed to achieve VO 2max , mathematical adjustments were made to analyze VO 2 kinetics during the Tlim using mono-exponential functions as suggested by Jones et al (2008) and described in the following equation:…”

Section: Methodsmentioning

confidence: 99%

Physiological Responses During the Time Limit at 100% of the Peak Velocity in the Carminatti’s Test in Futsal Players

Floriano

Silva

Teixeira

et al. 2016

Journal of Human Kinetics

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The aim of this study was to investigate the physiological responses during the time limit at the intensity of the peak velocity of the Carminatti’s test (T-CAR). Ten professional futsal players (age, 27.4 ± 5.8 years, body mass, 78.8 ± 8.5 kg, body height, 175.8 ± 6.8 cm, body fat mass, 14.1 ± 2.6%) took part in the study. The players performed three tests, with an interval of at least 48 hours, as follows: the T-CAR to determine the peak velocity and the maximal heart rate; an incremental treadmill protocol to determine the maximal physiological responses; and a time limit running test at the peak velocity reached in the T-CAR. During the last two tests, a portable gas analyzer was used for direct measurement of cardiorespiratory variables. It was shown that the peak velocity was not significantly different from the maximal aerobic speed achieved in the laboratory (p = 0.213). All athletes reached their maximum oxygen uptake during the time limit test. The maximum oxygen uptake achieved during the time limit test was not different from that observed in the laboratory condition (51.1 ± 4.7 vs. 49.6 ± 4.7 ml·kg-1·min-1, respectively, p = 0.100). In addition, Bland and Altman plots evidenced acceptable agreement between them. On average, athletes took ~140 s to achieve maximum oxygen uptake and maintained it for ~180 s. Therefore, the peak velocity intensity can be used as an indicator of maximal aerobic power of futsal athletes and the time limit can be used as a reference for training prescription.

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Section: Methodsmentioning

confidence: 99%

Physiological Responses During the Time Limit at 100% of the Peak Velocity in the Carminatti’s Test in Futsal Players

Floriano

Silva

Teixeira

et al. 2016

Journal of Human Kinetics

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“…However, previous research has employed both low and high intensity cycling protocols prior to 260 running and have reported little or no significant change to muscle recruitment patterns (Bonacci et al, 2011). Similar evidence has stated that prior submaximal or moderate intensity exercise is not sufficient to influence subsequent physiological variables, including the speeding of V O 2 (Gerbino, Ward, & Whipp, 1996;Jones et al, 2008). Our results show that V O 2 values at t 1/2 and MRT are significantly 265 reduced in time (Table 3) and are likely due to the elevated metabolic starting point during the C-R condition.…”

Section: Discussionmentioning

confidence: 83%

Neuromuscular and physiological variables evolve independently when running immediately after cycling

Stapley

Stamenkovic

Lepers

et al. 2015

Journal of Electromyography and Kinesiology

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During the early period of running after cycling, EMG patterns of the leg are modified in only some highly trained triathletes. The majority of studies have analysed muscle EMG patterns at arbitrary, predetermined time points. The purpose of this study was to examine changes to EMG patterns of the lower limb at physiologically determined times during the cycle-run transition period to better investigate neuromuscular adaptations. Six highly trained triathletes completed a 10 min isolated run (IR), 30 min of rest, then a 20 min cycling procedure, before a 10 min transition run (C-R). Surface EMG activity of eight lower limb muscles was recorded, normalised and quantified at four time points. Oxygen uptake and heart rate values were also collected. Across all muscles, mean (±SD) EMG patterns, demonstrated significant levels of reproducibility for each participant at all four time points (α < 0.05; r = 0.52-0.97). Mean EMG patterns during C-R correlated highly with the IR patterns (α < 0.05). These results show that EMG patterns during subsequent running are not significantly affected by prior cycling. However, variability of muscle recruitment activity does appear to increase during C-R transition when compared to IR. Disciplines Medicine and Health Sciences | Social and Behavioral Sciences AbstractDuring the early period of running after cycling, EMG patterns of the leg are modified in only some highly trained triathletes. The majority of studies have analysed muscle EMG patterns at arbitrary, predetermined time points. The purpose of this study was to examine changes to EMG patterns of the lower limb at physiologically determined times during the cycle-run transition period to better investigate neuromuscular adaptations. Six highly trained triathletes completed a 10 min isolated run (IR), 30 min of rest, then a 20 min cycling procedure, before a 10 min transition run (C-R). Surface EMG activity of eight lower limb muscles was recorded, normalised and quantified at four time points. Oxygen uptake and heart rate values were also collected. Across all muscles, mean (±SD) EMG patterns, demonstrated significant levels of reproducibility for each participant at all four time points (α < 0.05; r = 0.52 -0.97). Mean EMG patterns during C-R correlated highly with the IR patterns (α < 0.05). These results show that EMG patterns during subsequent running are not significantly affected by prior cycling. However, variability of muscle recruitment activity does appear to increase during C-R transition when compared to IR.

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“…Potentially, this could impact upon our proposed TRIMPS score particularly for the determination of v max . Priming exercise, however, seems to be specific to the exercise modality and has not been found in running (Jones et al 2008). On this evidence we feel that, for running at least, our TRIMPS score should be sufficiently robust, however, it would be prudent to ensure that no exercise in the very heavy domain is used prior to the trials to establish the speed-duration relationship.…”

Section: Discussionmentioning

confidence: 90%

A mathematical model for quantifying training

Hayes

Quinn

2009

Eur J Appl Physiol

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A systems modelling approach has been used to quantify the dose-response nature of training. Considerable attention has been focused on the modelling process with little work on the determination of the training impulse (TRIMP) scores. Currently, the methods employed to calculate TRIMPs are subject to various limitations including the use of generic ordinal category or exponential weighting factors for higher exercise intensities. These weightings are necessary to prevent excessively high scores from long duration, low intensity bouts of exercise. We propose a new method to calculate TRIMP scores based upon a whole body bioenergetic model. Our method is individual specific, removing many of the previous limitations. Furthermore, this model could enable a greater comparison of continuous and interval training methods. This model takes into account the length of repetition(s), concentration of the interval session and mode of recovery. This approach, while requiring further research, offers a potential improvement in the accuracy of training load calculations.

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‘Priming’ exercise and O2 uptake kinetics during treadmill running

Cited by 23 publications

References 57 publications

Physiological Responses During the Time Limit at 100% of the Peak Velocity in the Carminatti’s Test in Futsal Players

Physiological Responses During the Time Limit at 100% of the Peak Velocity in the Carminatti’s Test in Futsal Players

Neuromuscular and physiological variables evolve independently when running immediately after cycling

A mathematical model for quantifying training

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