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Human Wear Trials for Assessing Comfort Performance of Firefighter Protective Clothing
Published in Guowen Song, Faming Wang, Firefighters’ Clothing and Equipment, 2018
The rate of metabolic heat production (M) is correlated well with the respiratory exchange ratio (RQ) and rate of oxygen consumption (VO2). It can be calculated as (Gagge and Nishi, 1977; Gagge and Gonzalez, 1996; Leyenda et al., 2017) M=5.873⋅VO2⋅(60/AD){0.23RQ+0.77}(W/m2)
Metabolic Testing Principles for Optimizing Performance Testing and Training Goals in Sport and Exercise
Published in Youlian Hong, Routledge Handbook of Ergonomics in Sport and Exercise, 2013
Many of these systems use interpretation algorithms for analysing raw test data into basic reporting templates to simplify the tester-to-client reporting process. These templates provide information such as current cardiovascular fitness level, ventilatory threshold or functional thresholds (termed aerobic threshold in performance-based systems), respiratory compensation (termed anaerobic threshold in performance-based systems) and a client’s corresponding heart rate or watt training zones depending on the ergometer tool used for testing. To gain a competitive edge on the competition, some metabolic cart manufacturers have developed novel uses for metabolic testing parameters, such as plotting whole-body fat oxidation rates based on a person’s respiratory exchange ratio (RER) and oxygen uptake responses during an incremental metabolic profiling test from rest to near or maximal exercise effort. Post-testing, the client is provided a training zone report that identifies the estimated ideal fat burn zone according to the testing results. While the use of RER for determining a person’s fat-to-carbohydrate utilization crossover point is supported in the literature (Brooks, 1997; Brooks and Mercier, 1994), data regarding the reliability of the testing protocols or the implied benefits on performance improvements before and after a training period are not found in the literature.
In-Vivo Physiologic Evaluation of Murine Cardiovascular Phenotypes
Published in Robert J. Gropler, David K. Glover, Albert J. Sinusas, Heinrich Taegtmeyer, Cardiovascular Molecular Imaging, 2007
Carla J. Weinheimer, Attila Kovacs, Michael Courtois, Carolyn Mansfield
Figure 7 shows the importance of precisely defining the time point at which certain measurements, such as oxygen consumption are taken. In this protocol, mice are placed in a closed non-moving treadmill system and baseline (resting) measurements are taken to determine oxygen consumption levels and the respiratory exchange ratio (RER). It is difficult to determine resting conditions in a mouse. Figure 7 shows that while the RER is stable from time zero to one hour, the oxygen consumption continues to fall from roughly 11 ml/hr/g to under 8 ml/hr/g in this period. Specific parameters such as resting oxygen consumption are probably not achieved until mice are left undisturbed for over a 1 hr period. In addition, data from Figure 7 emphasizes the need for well-defined inclusion criteria. While 11 of the 12 mice in this study settled down after a 60 minute period and baseline values could be assessed, one mouse (top dotted line) remained agitated by visual assessment and clearly manifested elevated oxygen consumption levels. This is a mouse that should probably be excluded from the study.
The effect of exercise interventions on resting metabolic rate: A systematic review and meta-analysis
Published in Journal of Sports Sciences, 2020
Kristen MacKenzie-Shalders, Jaimon T. Kelly, Daniel So, Vernon G. Coffey, Nuala M. Byrne
Human energy expenditure has three primary components: activity energy expenditure, resting metabolic rate (RMR) and dietary-induced thermogenesis (DIT) (Levine, 2005). The accurate measurement and interpretation of RMR is beneficial as it is a principal contributor to daily energy expenditure. In practice, this is usually measured by Indirect Calorimetry, a method that is “indirect” as it measures airflow and the percentage of oxygen (O2) and carbon dioxide (CO2) to generate the respiratory exchange ratio (RER) which is subsequently converted to energy expended through known relationships (Levesey, 1988; Lusk, 1924). It is important for practitioners to understand how behaviours and lifestyle can impact on components of energy expenditure, in particular, the effect of exercise on RMR is of interest as it has implications for health and sports performance. Despite this, there is a lack of agreement in the literature regarding the potential for exercise to modulate RMR in humans.
Metabolic and kinematic responses while walking and running on a motorised and a curved non-motorised treadmill
Published in Journal of Sports Sciences, 2019
Paolo Bruseghini, Enrico Tam, Andrea Monte, Carlo Capelli, Paola Zamparo
Each participant performed a maximal incremental exercise test on both MT and CNMT consisting of: i) 3 min at rest (standing on treadmill); ii) 3 min of warm-up at PWS, iii) steps where speed was increased by 0.28 m · s−1 (e.g. 1 km · h−1) each minute (starting from 1.67 m · s−1) until voluntary exhaustion. The speed on MT was automatically increased by using MT software, whereas the speed on CNMT was adjusted by the participant “on command”: verbal feedback on speed was provided to the participant by a technician who monitored the speed output in real time using a customised software (Curve Software, Version 1.32; World Wide Software Solutions Inc., Milwaukee, USA) in order to maintain the target speed. Speed data on CNMT were averaged every 1-min in each completed stage. Throughout the tests, oxygen uptake , heart rate (HR), minute ventilation and respiratory exchange ratio (RER) were recorded continuously using a metabolic cart. Rating of perceived exertions (RPE) were recorded during the final 15 s of each stage by asking the subjects to select the level of perceived effort on a Borg CR-10 scale presented by the operator. Before the exercise and 1, 3, 5 and 7 min after the end of exercise, a blood sample was collected from the ear lobe and analysed for lactate concentration ([La]) (Biosen C-line, EKF diagnostic GmbH, Barleben, Germany); the highest of the four readings was taken as peak lactate value: [La]peak.
Running economy and effort after cycling: Effect of methodological choices
Published in Journal of Sports Sciences, 2020
Chantelle du Plessis, Anthony J. Blazevich, Chris Abbiss, Jodie Cochrane Wilkie
In contrast, some research suggests that cycling does not meaningfully impact running economy or alter biomechanical variables (Bonacci et al., 2011; Millet et al., 2000). The reason for this discrepancy is difficult to determine because different study methods have been used, including the test protocols adopted, the level of running intensity relative to participating athlete’s race velocity, the level of participating athletes, data averaging techniques implemented, and gas analysis systems used to measure oxygen consumption. Another particularly important factor complicating study comparisons is the method used to quantify running economy. For example, running economy has most commonly been expressed in triathlon studies as the V̇O2 per unit time (mL∙kg−1∙min−1) (Bonacci et al., 2010; Etxebarria, Hunt, et al., 2014; Hue et al., 1997) or as EO2 (mL∙kg−1∙m−1) (Pialoux et al., 2008; Suriano et al., 2007) when running at a given submaximal velocity. Alternatively, the calculation of energy cost (Eaer, J∙kg−1∙m−1) (Hausswirth et al., 1997; Millet et al., 2000) has been postulated to be a more valid measure of running economy as it is sensitive to alterations in substrate utilisation (Kipp et al., 2018; Di Prampero et al., 2009; Shaw et al., 2013). This is due to the energy equivalent of oxygen varying depending on the substrate metabolized (i.e., the relative quantity of carbohydrate and fat oxidation) and the exercise intensity. In order to quantify energy expenditure during metabolic steady-state exercise, the respiratory exchange ratio (RER) can be calculated when the mixture of fuels oxidized for energy is known (Fletcher et al., 2009; Kipp et al., 2018). Since this is not accounted for in V̇O2 and EO2 calculations (Saunders et al., 2004a), Eaer is considered to reflect the true energy expenditure and should therefore be more indicative of individual responses when running at different relative intensities or when running is preceded by cycling. An examination of the effects of running economy calculation method may therefore help to explain contradictory findings regarding the effect of cycling on subsequent running economy.