Sports Medicine

, Volume 40, Issue 2, pp 95–111 | Cite as

Recommendations for Improved Data Processing from Expired Gas Analysis Indirect Calorimetry

  • Robert A. RobergsEmail author
  • Dan Dwyer
  • Todd Astorino
Current Opinion


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 (V̇O2) 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, FEO2 and FECO2, respectively. Based on the results of explanation of variance of the breath-by-breath V̇O2 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 V̇O2 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 V̇O2 (V̇O2max) 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, FEO2 and FECO2 removed 96–98% of V̇O2 breath-by-breath variability in incremental and steady-state exercise V̇O2 data sets, respectively. Correction of residual error in V̇O2 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.


Digital Filter Respiratory Exchange Ratio Indirect Calorimetry Incremental Exercise Exercise Physiologist 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



No sources of funding were used to assist in the preparation of this review. The authors have no conflicts of interest that are directly relevant to the content of this review.


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Copyright information

© Adis Data Information BV 2010

Authors and Affiliations

  1. 1.Exercise and Sports SciencesUniversity of Western SydneySydneyAustralia
  2. 2.Exercise Physiology LaboratoriesUniversity of New MexicoAlbuquerqueUSA
  3. 3.Exercise ScienceUniversity of NewcastleNewcastleAustralia
  4. 4.Department of KinesiologyCalifornia State UniversitySan MarcosUSA

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