Evaluating Airflow Sensor Methods: Precision in Indirect Calorimetry

Abstract

This study assesses the impact of three volumetric gas flow measurement methods—turbine (fT); pneumotachograph (fP), and Venturi (fV)—on predictive accuracy and precision of expired gas analysis indirect calorimetry (EGAIC) across varying exercise intensities. Six males (Age: 38 ± 8 year; Height: 178.8 ± 4.2 cm; : 42 ± 2.8 mL O2 kg−1 min−1) and 14 females (Age = 44.6 ± 9.6 year; Height = 164.6 ± 6.9 cm; = 45 ± 8.6 mL O2 kg−1 min−1) were recruited. Participants completed physical exertion on a stationary cycle ergometer for simultaneous pulmonary minute ventilation () measurements and EGAIC computations. Exercise protocols and subsequent conditions involved a 5‐min cycling warm‐up at 25 W min−1, incremental exercise to exhaustion ( ramp test), then a steady‐state exercise bout induced by a constant Watt load equivalent to 80% ventilatory threshold (80% VT). A linear mixed model revealed that exercise intensity significantly affected measurements (p < 0.0001), whereas airflow sensor method (p = 0.97) and its interaction with exercise intensity (p = 0.91) did not. Group analysis of precision yielded a CV % = 21%; SEM = 5 mL O2 kg−1 min−1. Intra‐ and interindividual analysis of precision via Bland–Altman revealed a 95% confidence interval (CI) precision benchmark of 3–5 mL kg−1 min−1. Agreement among methods decreased at power outputs eliciting up to 150 L min−1, indicating a decrease in precision and highlighting potential challenges in interpreting biological variability, training response heterogeneity, and test–retest comparisons. These findings suggest careful consideration of airflow sensor method variance across metabolic cart configurations.