Cardiorespiratory kinetics: comparisons between athletes with different training habits

Adaptations to 4 weeks of high-intensity interval training in healthy adults with different training backgrounds

PURPOSE

This study investigated the physical fitness and oxygen uptake kinetics ([Formula: see text]) along with the exercise-onset O₂ delivery (heart rate kinetics, τHR; changes in normalized deoxyhemoglobin/[Formula: see text] ratio, Δ[HHb]/[Formula: see text]) adaptations of individuals with different physical activity (PA) backgrounds responding to 4 weeks of high-intensity interval training (HIIT), and the possible effects of skeletal muscle mass (SMM) on training-induced adaptations.

METHODS

Twenty subjects (10 high-PA level, HIIT-H; 10 moderate-PA level, HIIT-M) engaged in 4 weeks of treadmill HIIT. Ramp-incremental (RI) test and step-transitions to moderate-intensity exercise were performed. Cardiorespiratory fitness, body composition, muscle oxygenation status, VO₂ and HR kinetics were assessed at baseline and post-training.

RESULTS

HIIT improved fitness status for HIIT-H ([Formula: see text], + 0.26 ± 0.07 L/min; SMM, + 0.66 ± 0.70 kg; body fat, - 1.52 ± 1.93 kg; [Formula: see text], - 7.11 ± 1.05 s, p < 0.05) and HIIT-M ([Formula: see text], 0.24 ± 0.07 L/min, SMM, + 0.58 ± 0.61 kg; body fat, - 1.64 ± 1.37 kg; [Formula: see text], - 5.48 ± 1.05 s, p < 0.05) except for visceral fat area (p = 0.293) without between-group differences (p > 0.05). Oxygenated and deoxygenated hemoglobin amplitude during the RI test increased for both groups (p < 0.05) except for total hemoglobin (p = 0.179). The Δ[HHb]/[Formula: see text] overshoot was attenuated for both groups (p < 0.05) but only eliminated in HIIT-H (1.05 ± 0.14 to 0.92 ± 0.11), and no change was observed in τHR (p = 0.144). Linear mixed-effect models presented positive effects of SMM on absolute [Formula: see text] (p < 0.001) and ΔHHb (p = 0.034).

CONCLUSION

Four weeks of HIIT promoted positive adaptations in physical fitness and [Formula: see text] kinetics, with the peripheral adaptations attributing to the observed improvements. The training effects are similar between groups suggesting that HIIT is effective for reaching higher physical fitness levels.

Cardiorespiratory kinetics in exercise physiology: estimates and predictions using randomized changes in work rate

Purpose

Kinetics of cardiorespiratory parameters (CRP) in response to work rate (WR) changes are evaluated by pseudo-random binary sequences (PRBS testing). In this study, two algorithms were applied to convert responses from PRBS testing into appropriate impulse responses to predict steady states values and responses to incremental increases in exercise intensity.

Methods

13 individuals (age: 41 ± 9 years, BMI: 23.8 ± 3.7 kg m⁻²), completing an exercise test protocol, comprising a section of randomized changes of 30 W and 80 W (PRBS), two phases of constant WR at 30 W and 80 W and incremental WR until subjective fatigue, were included in the analysis. Ventilation (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}_{{\text{E}}}$$\end{document}V˙E), O₂ uptake (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{2}$$\end{document}V˙O2), CO₂ output (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{CO}}_{2}$$\end{document}V˙CO2) and heart rate (HR) were monitored. Impulse responses were calculated in the time domain and in the frequency domain from the cross-correlations of WR and the respective CRP.

Results

The algorithm in the time domain allows better prediction for \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{2}$$\end{document}V˙O2 and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{CO}}_{2}$$\end{document}V˙CO2, whereas for \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}_{{\text{E}}}$$\end{document}V˙E and HR the results were similar for both algorithms. Best predictions were found for \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{2}$$\end{document}V˙O2 and HR with higher (3–4%) 30 W steady states and lower (1–4%) values for 80 W. Tendencies were found in the residuals between predicted and measured data.

Conclusion

The CRP kinetics, resulting from PRBS testing, are qualified to assess steady states within the applied WR range. Below the ventilatory threshold, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{2}$$\end{document}V˙O2 and HR responses to incrementally increasing exercise intensities can be sufficiently predicted.

Influence of the fitting window on the O2 uptake kinetics at the onset of moderate intensity exercise

The O₂ uptake (V̇o₂) data at the onset of an exercise are usually fitted with a mono-exponential function, after removal of the data pertaining to a conventional initial time period (ΔTr) lasting ∼20 s. We performed a thorough quantitative analysis on the effects of removing data pertaining to different ΔTr, aiming at identifying an objective method to establish the appropriate ΔTr. Breath-by-breath O₂ uptake responses, acquired from 25 healthy adults performing a step moderate-intensity exercise, and 10⁴ simulated biexponential responses, were analyzed. For all the responses, the kinetic parameters of a mono-exponential function and the corresponding asymptotic standard errors (ASEs) were estimated by nonlinear regression, removing the data pertaining to progressively longer initial periods (1 s each) up to 60 s. Four methods to establish objectively ΔTr were compared. The minimum estimated τ was obtained for ΔTr ≅ 35 s in both the V̇o₂ and simulated data, that was about 30% lower compared with that obtained for ΔTr ≅ 0s. The average ASE values remained quite constant up to ΔTr ≅ 35 s, thereafter they increased remarkably. The τ used to generate the simulated response fell within the confidence intervals of the estimated τ in ∼85% of cases for ΔTr = 20 s ("20 s-w" method); this percentage increased to ∼92% of cases when ΔTr was established according to both the minimum τ and its narrowest confidence interval ("Mixed" method). In conclusion, the effects of removing V̇o₂ data pertaining to different ΔTr are remarkable. The "Mixed" method provided estimated parameters close to those used to generate the simulated responses and is thus endorsed.NEW & NOTEWORTHY We propose a method to objectively establish the initial time period to be removed from the fitting window when, using a mono-exponential model, the kinetics of the fundamental component is determined on breath-by-breath O₂ uptake data collected at the onset of a moderate-intensity exercise. Innovative statistical parameters ("Coverage" and "Concordance_5%," applicable on simulated responses) were used to compare its performance with that of other three methods. The proposed method yielded the best "Coverage" and "Concordance_5%."

Relationship between maximal aerobic power with aerobic fitness as a function of signal-to-noise ratio

Efforts to better understand cardiorespiratory health are relevant for the future development of optimized physical activity programs. We aimed to explore the impact of the signal quality on the expected associations between the ability of the aerobic system in supplying energy as fast as possible during moderate exercise transitions with its maximum capacity to supply energy during maximal exertion. It was hypothesized that a slower aerobic system response during moderate exercise transitions is associated with a lower maximal aerobic power; however, this relationship relies on the quality of the oxygen uptake data set. Forty-three apparently healthy participants performed a moderate constant work rate (CWR) followed by a pseudorandom binary sequence (PRBS) exercise protocol on a cycle ergometer. Participants also performed a maximum incremental cardiopulmonary exercise testing (CPET). The maximal aerobic power was evaluated by the peak oxygen uptake during the CPET, and the aerobic fitness was estimated from different approaches for oxygen uptake dynamics analysis during the CWR and PRBS protocols at different levels of signal-to-noise ratio. The product moment correlation coefficient was used to evaluate the correlation level between variables. Aerobic fitness was correlated with maximum aerobic power, but this correlation increased as a function of the signal-to-noise ratio. Aerobic fitness is related to maximal aerobic power; however, this association appeared to be highly dependent on the data quality and analysis for aerobic fitness evaluation. Our results show that simpler moderate exercise protocols might be as good as maximal exertion exercise protocols to obtain indexes related to cardiorespiratory health.NEW & NOTEWORTHY Optimized methods for cardiorespiratory health evaluation are of great interest for public health. Moderate exercise protocols might be as good as maximum exertion exercise protocols to evaluate cardiorespiratory health. Pseudorandom or constant workload moderate exercise can be used to evaluate cardiorespiratory health.

5 km front crawl in pool and open water swimming: breath-by-breath energy expenditure and kinematic analysis

PURPOSE

Breath-by-breath energy expenditure during open water swimming has not yet been explored in an ecological environment. This study aimed to investigate and compare energetics and kinematics of 5 km swimming, in both swimming pool and open water conditions.

METHODS

Through four independent studies, oxygen uptake ([Formula: see text]₂) kinetics, heart rate (HR), blood lactate concentration ([La^-]) and glucose level (BGL), metabolic power ([Formula: see text]), energy cost (C) and kinematics were assessed during 5 km front crawl trials in a swimming pool and open water conditions. A total of 38 competitive open water swimmers aged 16-27 years volunteered for this four part investigation: Study A (pool, ten females, 11 males), Study B (pool, four females, six males), Study C (pool case study, one female) and Study D (open water, three females, four males).

RESULTS

In the swimming pool, swimmers started with an above average swimming speed (v), losing efficiency along the 5 km, despite apparent homeostasis for [La^-], BGL, [Formula: see text]₂, [Formula: see text] and C. In open water, swimmers started the 5 km with a below average v, increasing the stroke rate (SR) in the last 1000 m. In open water, [Formula: see text]₂ kinetics parameters, HR, [La^-], BGL, respiratory exchange ratio and C were affected by the v and SR fluctuations along the 5 km.

CONCLUSIONS

Small fluctuations were observed for energetic variables in both conditions, but changes in C were lower in swimming pool than in open water. Coaches should adjust the training plan accordingly to the specificity of open water swimming.

Breath-by-breath oxygen uptake during running: Effects of different calculation algorithms

NEW FINDINGS

What is the central question of this study? Breath-by-breath gas exchange analysis during treadmill exercise can be disturbed by different breathing patterns depending on cadence, and the flow sensor might be subjected to variable mechanical stress. It is still unclear whether the outcomes of the gas exchange algorithms can be affected by running at different speeds. What is the main finding and its importance? Practically, the three investigated breath-by-breath algorithms ('Wessel', 'expiration-only' and 'independent breath') provided similar average gas exchange values for steady-state conditions. The 'independent breath' algorithm showed the lowest breath-by-breath fluctuations in the gas exchange data compared with the other investigated algorithms, both at steady state and during incremental exercise.

ABSTRACT

Recently, a new breath-by-breath gas exchange calculation algorithm (called 'independent breath') was proposed. In the present work, we aimed to compare the breath-by-breath O₂ uptake ( V ̇ O 2 ) values assessed in healthy subjects undergoing a running protocol, as calculated applying the 'independent breath' algorithm or two other commonly used algorithms. The traces of respiratory flow, O₂ and CO₂ fractions, used by the calculation algorithms, were acquired at the mouth on 17 volunteers at rest, during running on a treadmill at 6.5 and 9.5 km h^-1 , and thereafter up to volitional fatigue. Within-subject averages and standard deviations of breath-by-breath V ̇ O 2 were calculated for steady-state conditions; the V ̇ O 2 data of the incremental phase were analysed by means of linear regression, and their root mean square was assumed to be an index of the breath-by-breath fluctuations. The average values obtained with the different algorithms were significantly different (P < 0.001); nevertheless, from a practical point of view the difference could be considered 'small' in all the investigated conditions (effect size <0.3). The standard deviations were significantly lower for the 'independent breath' algorithm (post hoc contrasts, P < 0.001), and the slopes of the relationships with the corresponding data yielded by the other algorithms were <0.70. The root mean squares of the linear regressions calculated for the incremental phase were also significantly lower for the 'independent breath' algorithm, and the slopes of the regression lines with the corresponding values obtained with the other algorithms were <0.84. In conclusion, the 'independent breath' algorithm yielded the least breath-by-breath O₂ uptake fluctuation, both during steady-state exercise and during incremental running.