Date Published: January 4, 2016
Publisher: Public Library of Science
Author(s): Rômulo Bertuzzi, Jorge Melegati, Salomão Bueno, Thaysa Ghiarone, Leonardo A. Pasqua, Arthur Fernandes Gáspari, Adriano E. Lima-Silva, Alfredo Goldman, Jonathan Peterson.
The aim of the current study is to describe the functionality of free software developed for energy system contributions and energy expenditure calculation during exercise, namely GEDAE-LaB.
Eleven participants performed the following tests: 1) a maximal cycling incremental test to measure the ventilatory threshold and maximal oxygen uptake (V˙O2max); 2) a cycling workload constant test at moderate domain (90% ventilatory threshold); 3) a cycling workload constant test at severe domain (110% V˙O2max). Oxygen uptake and plasma lactate were measured during the tests. The contributions of the aerobic (AMET), anaerobic lactic (LAMET), and anaerobic alactic (ALMET) systems were calculated based on the oxygen uptake during exercise, the oxygen energy equivalents provided by lactate accumulation, and the fast component of excess post-exercise oxygen consumption, respectively. In order to assess the intra-investigator variation, four different investigators performed the analyses independently using GEDAE-LaB. A direct comparison with commercial software was also provided.
All subjects completed 10 min of exercise at moderate domain, while the time to exhaustion at severe domain was 144 ± 65 s. The AMET, LAMET, and ALMET contributions during moderate domain were about 93, 2, and 5%, respectively. The AMET, LAMET, and ALMET contributions during severe domain were about 66, 21, and 13%, respectively. No statistical differences were found between the energy system contributions and energy expenditure obtained by GEDAE-LaB and commercial software for both moderate and severe domains (P > 0.05). The ICC revealed that these estimates were highly reliable among the four investigators for both moderate and severe domains (all ICC ≥ 0.94).
These findings suggest that GEDAE-LaB is a free software easily comprehended by users minimally familiarized with adopted procedures for calculations of energetic profile using oxygen uptake and lactate accumulation during exercise. By providing availability of the software and its source code we hope to facilitate future related research.
The establishment of the amount of energy expenditure during exercise has been considered of key importance for strategy development aiming at both health  and athletic performance  improvement. Over the past century, many methods have emerged in literature in order to assess energetic profiles during dynamic exercise [3,4]. It has been widely accepted that whole-body oxygen uptake (V˙O2) can be used to represent aerobic system contribution (AMET) . On the other hand, there is no universal method accepted as gold standard to estimate anaerobic system contribution [5,6]. It has been proposed that measurements of muscle metabolites using biopsy could provide relevant information regarding alactic (ALMET) and lactic (LAMET) anaerobic systems . Aside from being an invasive procedure, the small sample size taken in the biopsy for the determination of maximum amount of ATP that can be resynthesized by anaerobic system might result in an inaccurate estimative . Thus, alternative methods using whole-body physiological variables have been proposed in order to estimate the anaerobic system contribution (ALMET and LAMET) during dynamic exercises.
Physiological and mechanical parameters measured during maximal incremental exercise test are shown in Table 1. Power output measured at moderate and severe domains were 99.1 ± 13.6 W and 279.5 ± 40.6 W, respectively. All subjects completed the 10 min of exercise at moderate domain, while the time to exhaustion at severe domain was 144 ± 65 s. The mean of [La-]peak measured during moderate and severe domains were 2.3 ± 0.3 mmol∙l-1 and 7.5 ± 2.2 mmol∙l-1, respectively.
The estimate of energy expenditure is useful for the evaluation of acute and chronic effects of exercise in athletic performance and daily life. An understanding of energy metabolism involved in an athletic event or in daily activity is important for the correct structuring of strategies that target both health and athletic performances. However, the determination of energetic profiles using physiological data often require the use of some mathematical functions that may be considered unusual to many exercise physiologists. For example, previous studies have fitted post-exercise V˙O2 kinetics using a bi- or a mono-exponential model to determine the ALMET during exercise [8,9,16]. This results in a more complex process to estimate the ALMET energy expenditure because the fitting of the exponential data requires the use of appropriate equations and initial reference values for each parameter, which are not frequently provided by the commercial software. Considering that available software are not free and were not designed especially for the determination of energy expenditure, processing physiological data for establishment of energy profile during exercise might be considered costly, time-consuming, expertise-requiring and error-prone in their use. Therefore, the current study introduced GEDAE-LaB as software specifically designed for estimation of energetic profiles during dynamic exercise.