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Recommendations for improved data processing from expired gas analysis indirect calorimetry

journal contribution
posted on 2010-02-01, 00:00 authored by R Robergs, Dan DwyerDan Dwyer, T Astorino
There is currently no universally recommended and accepted method of data processing within the science of indirect calorimetry for either mixing chamber or breath-by-breath systems of expired gas analysis. Exercise physiologists were first surveyed to determine methods used to process oxygen consumption ([OV0312]O 2) data, and current attitudes to data processing within the science of indirect calorimetry. Breath-by-breath datasets obtained from indirect calorimetry during incremental exercise were then used to demonstrate the consequences of commonly used time, breath and digital filter post-acquisition data processing strategies. Assessment of the variability in breath-by-breath data was determined using multiple regression based on the independent variables ventilation (VE), and the expired gas fractions for oxygen and carbon dioxide, FEO 2 and FECO2, respectively. Based on the results of explanation of variance of the breath-by-breath [OV0312]O2 data, methods of processing to remove variability were proposed for time-averaged, breath-averaged and digital filter applications. Among exercise physiologists, the strategy used to remove the variability in sequential [OV0312]O2 measurements varied widely, and consisted of time averages (30 sec [38%], 60 sec [18%], 20 sec [11%], 15 sec [8%]), a moving average of five to 11 breaths (10%), and the middle five of seven breaths (7%). Most respondents indicated that they used multiple criteria to establish maximum [OV0312]O 2 ([OV0312]O2max) including: the attainment of age-predicted maximum heart rate (HRmax) [53%], respiratory exchange ratio (RER) >1.10 (49%) or RER >1.15 (27%) and a rating of perceived exertion (RPE) of >17, 18 or 19 (20%). The reasons stated for these strategies included their own beliefs (32%), what they were taught (26%), what they read in research articles (22%), tradition (13%) and the influence of their colleagues (7%). The combination of VE, FEO 2 and FECO2 removed 96-98% of [OV0312]O2 breath-by-breath variability in incremental and steady-state exercise [OV0312]O2 data sets, respectively. Correction of residual error in [OV0312]O2 datasets to 10% of the raw variability results from application of a 30-second time average, 15-breath running average, or a 0.04 Hz low cut-off digital filter. Thus, we recommend that once these data processing strategies are used, the peak or maximal value becomes the highest processed datapoint. Exercise physiologists need to agree on, and continually refine through empirical research, a consistent process for analysing data from indirect calorimetry.



Sports medicine






95 - 111


Adis International


Aukland, New Zealand







Publication classification

C1.1 Refereed article in a scholarly journal

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2010, Adis International