4.5 Article

VO2, VCO2, and RQ in a respiratory chamber:: accurate estimation based on a new mathematical model using the Kalman-Bucy method

期刊

JOURNAL OF APPLIED PHYSIOLOGY
卷 96, 期 3, 页码 1045-1054

出版社

AMER PHYSIOLOGICAL SOC
DOI: 10.1152/japplphysiol.00788.2003

关键词

indirect calorimetry; respiratory gas exchange; energy expenditure; Kalman filter; stochastic model

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A respiratory chamber is used for monitoring O-2 consumption ((V) over dotO(2)), CO2 production ((V) over dotCO(2)), and respiratory quotient (RQ) in humans, enabling long term (24-h) observation under free-living conditions. Computation of (V) over dotO(2) and (V) over dotCO(2) is currently done by inversion of a mass balance equation, with no consideration of measurement errors and other uncertainties. To improve the accuracy of the results, a new mathematical model is suggested in the present study explicitly accounting for the presence of such uncertainties and error sources and enabling the use of optimal filtering methods. Experiments have been realized, injecting known gas quantities and estimating them using the proposed mathematical model and the Kalman-Bucy (KB) estimation method. The estimates obtained reproduce the known production rates much better than standard methods; in particular, the mean error when fitting the known production rates is 15.6 +/- 0.9 vs. 186 +/- 36 ml/min obtained using a conventional method. Experiments with 11 humans were carried out as well, where (V) over dotO(2) and (V) over dotCO(2) were estimated. The variance of the estimation errors, produced by the KB method, appears relatively small and rapidly convergent. Spectral analysis is performed to assess the residual noise content in the estimates, revealing large improvement: 2.9 +/- 0.8 vs. 3,440 +/- 824 (ml/min)(2) and 1.8 +/- 0.5 vs. 2,057 +/- 532 (ml/min)(2), respectively, for (V) over dotO(2) and (V) over dotCO(2) estimates. Consequently, the accuracy of the computed RQ is also highly improved (0.3 x 10(-4) vs. 800 x 10(-4)). The presented study demonstrates the validity of the proposed model and the improvement in the results when using a KB estimation method to resolve it.

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