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European Journal of Applied Physiology

Erschienen in:

04.05.2018 | Invited Review

Open-circuit respirometry: real-time, laboratory-based systems

verfasst von: Susan A. Ward

Erschienen in: European Journal of Applied Physiology | Ausgabe 5/2018

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Abstract

This review explores the conceptual and technological factors integral to the development of laboratory-based, automated real-time open-circuit mixing-chamber and breath-by-breath (B × B) gas-exchange systems, together with considerations of assumptions and limitations. Advances in sensor technology, signal analysis, and digital computation led to the emergence of these technologies in the mid-20th century, at a time when investigators were beginning to recognise the interpretational advantages of nonsteady-state physiological-system interrogation in understanding the aetiology of exercise (in)tolerance in health, sport, and disease. Key milestones include the ‘Auchincloss’ description of an off-line system to estimate alveolar O₂ uptake B × B during exercise. This was followed by the first descriptions of real-time automated O₂ uptake and CO₂ output B × B measurement by Beaver and colleagues and by Linnarsson and Lindborg, and mixing-chamber measurement by Wilmore and colleagues. Challenges to both approaches soon emerged: e.g., the influence of mixing-chamber washout kinetics on mixed-expired gas concentration determination, and B × B alignment of gas-concentration signals with respired flow. The challenging algorithmic and technical refinements required for gas-exchange estimation at the alveolar level have also been extensively explored. In conclusion, while the technology (both hardware and software) underpinning real-time automated gas-exchange measurement has progressively advanced, there are still concerns regarding accuracy especially under the challenging conditions of changing metabolic rate.

The interested reader is referred to some excellent reviews (e.g., Atkinson et al. 2005; Crouter et al. 2006; Hodges et al. 2005; Macfarlane 2001, 2017).

Conventionally, ventilation is measured as ‘expired’.

A nomenclature introduced by Whipp in 1978 which apportioned the nonsteady-state period following the onset of constant WR exercise into two distinct temporal domains, based on their underlying determinants of pulmonary gas exchange: phase 1, the initial short period in which pulmonary gas exchange is effectively isolated from the demands of increased muscle metabolic rate and is, therefore, dominated by increases in cardiac output or, more properly, pulmonary blood flow; and phase 2, having the additional challenge presented by the exercise-induced changes in mixed-venous blood composition. The eventual steady state is termed phase 3 (Whipp 1978).

A mixing chamber is a container within the expiratory line that operates as a temporary reservoir into which several consecutive expirates flow (the number depending on the chamber size). Their exit is delayed by having to travel past a series of baffles that both slow transit and promote turbulence, facilitating mixing of the dead space and alveolar components of each expirate. At the chamber outlet, a continuous aliquot of the resulting ‘mixed-expired’ gas is drawn into gas analysers for measurement.

Time required for a response to a step input to increase from 10 to 90% of its steady-state value.

As gas volumes are measured under ambient conditions, correction to STPD and BTPS conditions is required, as appropriate. For example, as \(\dot {V}{{\text{O}}_2}\) and \(\dot {V}{{\text{O}}_2}\) are referenced to STPD, \({\dot {V}_{\text{I}}}\) and \({\dot {V}_{\text{E}}}\) should be expressed as STPD for these particular calculations.

Time required for a response to attain 63% of its final value, with this being effectively attained within a time equal to ~ 4 time constants.

Time required for a response to attain 50% of its final value, with no assumptions being made about model order.

Deconvolution requires solution of the dynamic input–output relationship for the mixing chamber, by inversion of its transfer function (e.g., Finklestein and Carson 1985).

EDL, an XML application that provides a standard way of describing scientific experiments.

Ascribed variously to Harry Nyquist, Claude Shannon, Edmund Taylor Whittaker and Vladimir Kotelnikov (Kotelnikov 1933; Nyquist 1928; Shannon 1949; Whittaker 1915).

Employing lower digitisation frequencies, e.g., in the region of 25 Hz (Beaver et al. 1981), is likely to introduce anomolous dynamic distortions (‘aliasing’), such that different signals are no longer transformed uniquely (e.g., Bendat and Piersol 1986).

The decomposition of a function into its simple sinusoidal or harmonic components (e.g., Bendat and Piersol 1986).

The correlation of a signal with a lagged version of itself as a function of the lag time (e.g., Bendat and Piersol 1986).

An exception is when other inspirates are employed, e.g., hyperoxic, hypoxic, or hypercapnic (reviewed in Porszasz et al. 2007; Ward et al 2017).

More complex characteristics have also been explored (e.g., Arieli and Van Liew 1981; Mitchell 1979).

\({({V_{\text{I}}} \cdot {F_{\text{I}}}{{\text{N}}_2} - {\text{ }}{V_{\text{E}}} \cdot {F_{\overline {{\text{E}}} }}{{\text{N}}_2})^i} - {\text{ }}V_{{\text{A}}}^{{i - 1}}({F_{\text{A}}}{\text{N}}_{2}^{i} - {\text{ }}{F_{\text{A}}}{\text{N}}_{2}^{{i - 1}}){\text{ }}+{\text{ }}{F_{\text{A}}}N_{2}^{i}(V_{A}^{i} - {\text{ }}V_{A}^{{i - 1}}){\text{ }}={\text{ }}0\) and \({F_{\text{A}}}{\text{N}}_{2}^{i}(V_{{\text{A}}}^{i} - {\text{ }}V_{{\text{A}}}^{{i - 1}}){\text{ }}={({V_{\text{I}}} \cdot {F_{\text{I}}}{{\text{N}}_2} - {\text{ }}{V_{\text{E}}} \cdot {F_{\overline {{\text{E}}} }}{{\text{N}}_2})^i} - {\text{ }}V_{{\text{A}}}^{{i - 1}}({F_{\text{A}}}{\text{N}}_{2}^{i} - {\text{ }}{F_{\text{A}}}{\text{N}}_{2}^{{i - 1}})\).

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Titel: Open-circuit respirometry: real-time, laboratory-based systems
verfasst von: Susan A. Ward
Publikationsdatum: 04.05.2018
Verlag: Springer Berlin Heidelberg
Erschienen in: European Journal of Applied Physiology / Ausgabe 5/2018
Print ISSN: 1439-6319
Elektronische ISSN: 1439-6327
DOI: https://doi.org/10.1007/s00421-018-3860-9

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