Oxygen cost of dynamic leg exercise on a cycle ergometer: effects of gravity acceleration

Girardis, Massimo; Linnarsson, Dag; Moia, Christian; Pendergast, David R.; Ferretti, Guido

doi:10.1046/j.1365-201x.1999.00564.x

Cited by 15 publications

(19 citation statements)

References 25 publications

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“…Incidentally, both experiments were carried out at the same absolute submaximal powers and at the same pedalling frequency. Metabolic data from both studies have been previously published (Girardis et al 1999;Bonjour et al 2010). Cardiovascular data from the same studies are still unpublished.…”

Section: Introductionmentioning

confidence: 92%

“…The volume of the rebreathing bag was empirically established prior to the first experiment; it was increased with the exercise power output and ranged between 2.5 and 3.5 l. During rebreathing, the dry fractions of breathed gases at the mouth were continuously monitored by a photo-acoustic gas analyser (RMS-II, Innovision A/S, Odense, Denmark), stored on a magnetic disk and subsequently analysed by means of the Matlab computation software (Mathworks, USA). The knowledge of bag volume and initial bag SF 6 fraction allowed computation of the overall closed circuit volume, using the dilution principle, as previously described (Girardis et al 1999). _ V O 2 was then computed from the slope of the linear relation between the O 2 volume in the rebreathing bag at end of each expiration and the rebreathing time, as previously described (Girardis et al 1999).…”

Section: Steady-state _mentioning

confidence: 99%

“…Thus, experiments at higher or lower a g than on Earth are expensive, and consequently data obtained in those conditions are scanty. The evolution of space stations in the past 20 years and the installation of equipment, including cycle ergometers and respiratory monitoring systems, have allowed acquisition of some data in microgravity, parts of which have been published (Buderer et al 1976;Levine et al 1996;Michel et al 1977;Shykoff et al 1996;Girardis et al 1999). At high a g , although a few papers reporting metabolic data during exercise in a spinning human centrifuge can be found (Bjurstedt et al 1968;Nunneley and Shindell 1975;Nunneley 1976;Bonjour et al 2010), very little is known of the cardiovascular response to exercise.…”

Section: Introductionmentioning

confidence: 98%

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Effects of acceleration in the Gz axis on human cardiopulmonary responses to exercise

et al. 2011

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The aim of this paper was to develop a model from experimental data allowing a prediction of the cardiopulmonary responses to steady-state submaximal exercise in varying gravitational environments, with acceleration in the G(z) axis (a (g)) ranging from 0 to 3 g. To this aim, we combined data from three different experiments, carried out at Buffalo, at Stockholm and inside the Mir Station. Oxygen consumption, as expected, increased linearly with a (g). In contrast, heart rate increased non-linearly with a (g), whereas stroke volume decreased non-linearly: both were described by quadratic functions. Thus, the relationship between cardiac output and a (g) was described by a fourth power regression equation. Mean arterial pressure increased with a (g) non linearly, a relation that we interpolated again with a quadratic function. Thus, total peripheral resistance varied linearly with a (g). These data led to predict that maximal oxygen consumption would decrease drastically as a (g) is increased. Maximal oxygen consumption would become equal to resting oxygen consumption when a (g) is around 4.5 g, thus indicating the practical impossibility for humans to stay and work on the biggest Planets of the Solar System.

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Section: Introductionmentioning

confidence: 92%

Section: Steady-state _mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

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Effects of acceleration in the Gz axis on human cardiopulmonary responses to exercise

et al. 2011

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“…According to this equation, _ E I is independent of _ w. It was also demonstrated that _ E I is a power function of the pedalling frequency (f p ) (Francescato et al 1995) and is a linear function of the weight of the legs, that is the product of the mass of the legs (Ml) times the gravity acceleration (a g ) (Girardis et al 1999).…”

Section: The Mechanical Efficiency Of Exercisementioning

confidence: 95%

Aerobic Metabolism and the Steady-State Concept

Ferretti

2015

Energetics of Muscular Exercise

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This chapter contains an analysis of the steady-state concept, as it is applied during light exercise. In this case, oxygen consumption increases upon exercise onset to attain a steady level, which can be maintained for a long period of time. The steady-state oxygen consumption is proportional to the exerted mechanical power. Under these circumstances, there is neither accumulation of lactate in blood nor changes in muscle phosphocreatine concentration: aerobic metabolism sustains the entire energy requirement of the exercising body. Once the steady state has been attained, the flow of oxygen is the same at all levels along the respiratory system. The quantitative relations determining the flow of oxygen across the alveoli and in blood are discussed. Special attention is given to the effects of ventilation-perfusion inequality and to the diffusion-perfusion interaction equations. The cardiovascular responses at exercise steady state are analysed in the context of the equilibrium between systemic oxygen delivery and systemic oxygen return. The relationship between oxygen consumption and power is discussed, along with the distinction between external and internal work during cycling. The concepts of mechanical efficiency of exercise and energy cost of locomotion are analysed. Concerning the latter, the distinction between aerodynamic work and frictional work is introduced. The roles of the cross-sectional surface area on the frontal plane and of air density in aerodynamic work are discussed. To end with, an equation linking ventilation, circulation and metabolism at exercise in a tight manner is developed, around the notion that the homeostasis of the respiratory system at exercise is maintained around given values of the constant oxygen return. This equation tells that, as long as we are during steady-state exercise in normoxia, any increase in the exercise metabolic rate requires an increase in ventilation that is proportional to that in oxygen consumption only if the pulmonary respiratory quotient stays invariant does not change, and an increase in cardiac output that is not proportional to the corresponding increase in oxygen consumption. At intense exercise, when lactate accumulation also occurs and hyperventilation superimposes, a new steady state would be attained only at P A CO 2 values lower than 40 mmHg: the homeostasis of the respiratory system would be modified. This new steady state, however, is never attained in fact, for reasons that are discussed in Chap. 3.

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“…P int was estimated by measuring the mechanical or metabolic energy changes in various studies. The pedaling frequency (Foss and Hallen 2004;Hansen et al 2004;Minetti et al 2001;Prampero et al 1979;Hirakoba 2007, 2008), the mass of the legs (Francescato et al 1995;Kamon et al 1973), and the gravity acceleration (Bonjour et al 2010;Girardis et al 1999) Pint,kiñ Pint,met Fig. 2 The power cascade.…”

Section: Modelmentioning

confidence: 99%

Power–cadence relationship in endurance cycling

Emanuele

Denoth

2011

Eur J Appl Physiol

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In maximal sprint cycling, the power-cadence relationship to assess the maximal power output (P max ) and the corresponding optimal cadence (C opt ) has been widely investigated in experimental studies. These studies have generally reported a quadratic power-cadence relationship passing through the origin. The aim of the present study was to evaluate an equivalent method to assess P max and C opt for endurance cycling. The two main hypotheses were: (1) in the range of cadences normally used by cyclists, the power-cadence relationship can be well fitted with a quadratic regression constrained to pass through the origin; (2) P max and C opt can be well estimated using this quadratic fit. We tested our hypothesis using a theoretical and an experimental approach. The power-cadence relationship simulated with the theoretical model was well fitted with a quadratic regression and the bias of the estimated P max and C opt was negligible (1.0 W and 0.6 rpm). In the experimental part, eight cyclists performed an incremental cycling test at 70, 80, 90, 100, and 110 rpm to yield powercadence relationships at fixed blood lactate concentrations of 3, 3.5, and 4 mmol L -1 . The determined power outputs were well fitted with quadratic regressions (R 2 = 0.94-0.96, residual standard deviation = 1.7%). The 95% confidence interval for assessing individual P max and C opt was ±4.4 W and ±2.9 rpm. These theoretical and experimental results suggest that P max , C opt , and the power-cadence relationship around C opt could be well estimated with the proposed method.

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Oxygen cost of dynamic leg exercise on a cycle ergometer: effects of gravity acceleration

Cited by 15 publications

References 25 publications

Effects of acceleration in the Gz axis on human cardiopulmonary responses to exercise

Effects of acceleration in the Gz axis on human cardiopulmonary responses to exercise

Aerobic Metabolism and the Steady-State Concept

Power–cadence relationship in endurance cycling

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