Stability of the K4b² portable metabolic analyser during rest, walking and running

Accuracy of respiratory gas variables, substrate, and energy use from 15 CPET systems during simulated and human exercise

PURPOSE

Various systems are available for cardiopulmonary exercise testing (CPET), but their accuracy remains largely unexplored. We evaluate the accuracy of 15 popular CPET systems to assess respiratory variables, substrate use, and energy expenditure during simulated exercise. Cross-comparisons were also performed during human cycling experiments (i.e., verification of simulation findings), and between-session reliability was assessed for a subset of systems.

METHODS

A metabolic simulator was used to simulate breath-by-breath gas exchange, and the values measured by each system (minute ventilation [V̇E], breathing frequency [BF], oxygen uptake [V̇O2 ], carbon dioxide production [V̇CO2 ], respiratory exchange ratio [RER], energy from carbs and fats, and total energy expenditure) were compared to the simulated values to assess the accuracy. The following manufacturers (system) were assessed: COSMED (Quark CPET, K5), Cortex (MetaLyzer 3B, MetaMax 3B), Vyaire (Vyntus CPX, Oxycon Pro), Maastricht Instruments (Omnical), MGC Diagnostics (Ergocard Clinical, Ergocard Pro, Ultima), Ganshorn/Schiller (PowerCube Ergo), Geratherm (Ergostik), VO2master (VO2masterPro), PNOĒ (PNOĒ), and Calibre Biometrics (Calibre).

RESULTS

Absolute percentage errors during the simulations ranged from 1.15%-44.3% for V̇E, 1.05-3.79% for BF, 1.10%-13.3% for V̇O2 , 1.07%-18.3% for V̇CO2 , 0.62%-14.8% for RER, 5.52%-99.0% for Kcal from carbs, 5.13%-133% for Kcal from fats, and 0.59%-12.1% for total energy expenditure. Between-session variation ranged from 0.86%-21.0% for V̇O2 and 1.14%-20.2% for V̇CO2 , respectively.

CONCLUSION

The error of respiratory gas variables, substrate, and energy use differed substantially between systems, with only a few systems demonstrating a consistent acceptable error. We extensively discuss the implications of our findings for clinicians, researchers and other CPET users.

Optimization of VO2 and VCO2 outputs for the calculation of resting metabolic rate using a portable indirect calorimeter

This study aimed to compare the Cosmed K5 portable indirect calorimeter, using the mixing chamber mode and face mask, with a stationary metabolic cart when measuring the resting metabolic rate (RMR) and to derive fitting equations if discrepancies are observed. Forty-three adults (18-84 years) were assessed for their RMR for two 30-min consecutive and counterbalanced periods using a Cosmed K5 and an Oxycon Pro. Differences among devices were tested using paired sample Student's t-tests, and correlation and agreement were assessed using Pearson's correlation coefficients, intraclass correlation coefficient and Bland-Altman plots. Forward stepwise multiple linear regression models were performed to develop fitting equations for estimating differences among devices when assessing oxygen uptake (VO2 diff , mL·min-1 ) and carbon dioxide production (VCO2 diff , mL·min-1 ). Furthermore, the Oxycon Pro was tested before being confirmed as a reference device. Significant differences between devices were found in most metabolic and ventilatory parameters, including the primary outcomes of VO2 and VCO2 . These differences showed an overestimation of the Cosmed K5 in all metabolic outcomes, except for Fat, when compared to the Oxycon Pro. When derived fitting equations were applied (VO2 diff  - 139.210 + 0.786 [weight, kg] + 1.761 [height, cm] - 0.941 [Cosmed K5 VO2 , mL·min-1 ]; VCO2 diff  - 86.569 + 0.548 [weight, kg] + 0.915 [height, cm] - 0.728 [Cosmed K5 VCO2 , mL·min-1 ]), differences were minimized, and agreement was maximized. This study provides fitting equations which allow the use of the Cosmed K5 for reasonably optimal RMR determinations.

Physiological demands of running at 2-hour marathon race pace

The requirements of running a 2-h marathon have been extensively debated but the actual physiological demands of running at ∼21.1 km/h have never been reported. We therefore conducted laboratory-based physiological evaluations and measured running economy (O₂ cost) while running outdoors at ∼21.1 km/h, in world-class distance runners as part of Nike's "Breaking 2" marathon project. On separate days, 16 world-class male distance runners (age, 29 ± 4 yr; height, 1.72 ± 0.04 m; mass, 58.9 ± 3.3 kg) completed an incremental treadmill test for the assessment of V̇O_2peak, O₂ cost of submaximal running, lactate threshold and lactate turn-point, and a track test during which they ran continuously at 21.1 km/h. The laboratory-determined V̇O_2peak was 71.0 ± 5.7 mL/kg/min with lactate threshold and lactate turn-point occurring at 18.9 ± 0.4 and 20.2 ± 0.6 km/h, corresponding to 83 ± 5% and 92 ± 3% V̇O_2peak, respectively. Seven athletes were able to attain a steady-state V̇O₂ when running outdoors at 21.1 km/h. The mean O₂ cost for these athletes was 191 ± 19 mL/kg/km such that running at 21.1 km/h required an absolute V̇O₂ of ∼4.0 L/min and represented 94 ± 3% V̇O_2peak. We report novel data on the O₂ cost of running outdoors at 21.1 km/h, which enables better modeling of possible marathon performances by elite athletes. Using the value for O₂ cost measured in this study, a sub 2-h marathon would require a 59 kg runner to sustain a V̇O₂ of approximately 4.0 L/min or 67 mL/kg/min.NEW & NOTEWORTHY We report the physiological characteristics and O₂ cost of running overground at ∼21.1 km/h in a cohort of the world's best male distance runners. We provide new information on the absolute and relative O₂ uptake required to run at 2-h marathon pace.

Metabolic Costs of Standing and Walking in Healthy Military-Age Adults: A Meta-regression

INTRODUCTION

The Load Carriage Decision Aid (LCDA) is a U.S. Army planning tool that predicts physiological responses of soldiers during different dismounted troop scenarios. We aimed to develop an equation that calculates standing and walking metabolic rates in healthy military-age adults for the LCDA using a meta-regression.

METHODS

We searched for studies that measured the energetic cost of standing and treadmill walking in healthy men and women via indirect calorimetry. We used mixed effects meta-regression to determine an optimal equation to calculate standing and walking metabolic rates as a function of walking speed (S, m·s). The optimal equation was used to determine the economical speed at which the metabolic cost per distance walked is minimized. The estimation precision of the new LCDA walking equation was compared with that of seven reference predictive equations.

RESULTS

The meta-regression included 48 studies. The optimal equation for calculating normal standing and walking metabolic rates (W·kg) was 1.44 + 1.94S + 0.24S. The economical speed for level walking was 1.39 m·s (~ 3.1 mph). The LCDA walking equation was more precise across all walking speeds (bias ± SD, 0.01 ± 0.33 W·kg) than the reference predictive equations.

CONCLUSION

Practitioners can use the new LCDA walking equation to calculate energy expenditure during standing and walking at speeds <2 m·s in healthy, military-age adults. The LCDA walking equation avoids the errors estimated by other equations at lower and higher walking speeds.

Development of a Breath Analyzer for O2 and CO2 Measurement

Background:

Breath analysis can be used to screen disease and detect physical conditions. Many research studies have investigated various sensors or techniques that were used to detect gas concentrations and temperature. However, the studies were less concerned about the performance of sensors.

Methods:

In this study, we developed and tested a portable breath analyzer for exhaled gas measurement. We detected air flow rate, temperature, humidity, CO2 and O2 concentrations. Commercial sensing elements were used to assemble this breath analyzer. All sensors were calibrated to ensure their accuracy. The response times of different sensors were considered. We analyzed breath during three states; 1) seating and resting for 5 min, 2) walking for 5 min and 3) running for 5 min in test participants. Fifteen students 20 to 34 years of age were the test participants.

Results:

Heat, humidity and CO2 production and O2 consumption were calculated from these measured data and were used to assess the performance of the analyzer. The Respiratory Quotient (RQ) were estimated by the ratio of VCO2 to VO2. The RQ values for resting, walking and running states were 0.899, 0.865 and 0.785, respectively. Walking and running significantly increased the heat and humidity production of the human body, corresponding to the human physiological function.

Conclusion:

The RQ value is usually in the range of 0.8 to 0.85. The measurement results for our exhaled analyzer were close to this range. From the respiratory quotient values, the performance of this breath analyzer was reasonable.

Accuracy and Precision of the COSMED K5 Portable Analyser

The main aims of this study were to determine the accuracy of the portable metabolic cart K5 by comparison with a stationary metabolic cart (Vyntus CPX), to check on the validity of Vyntus CPX using a butane combustion test, and to assess the reliability of K5 during prolonged walks in the field. For validation, measurements were consecutively performed tests with both devices at rest and during submaximal exercise (bicycling) at low (60 W) and moderate intensities (130-160 W) in 16 volunteers. For the reliability study, 14 subjects were measured two times during prolonged walks (13 km, at 5 km/h), with the K5 set in mixing chamber (Mix) mode. Vyntus measured the stoichiometric RQ of butane combustion with high accuracy (error <1.6%) and precision (CV <0.5%), at VO₂ values between 0.788 and 6.395 L/min. At rest and 60 W, there was good agreement between Vyntus and K5 (breath-by-breath, B×B) in VO₂, VCO₂, RER, and energy expenditure, while in Mix mode the K5 overestimated VO₂ by 13.4 and 5.8%, respectively. Compared to Vyntus, at moderate intensity the K5 in B×B mode underestimated VO₂, VCO_2, and energy expenditure by 6.6, 6.9, and 6.6%, respectively. However, at this intensity there was an excellent agreement between methods in RER and fat oxidation. In Mix mode, K5 overestimated VO₂ by 5.8 and 4.8%, at 60 W and the higher intensity, respectively. The K5 had excellent reliability during the field tests. Total energy expenditure per Km was determined with a CV for repeated measurements of 4.5% (CI: 3.2-6.9%) and a concordance correlation coefficient of 0.91, similar to the variability in VO₂. This high reproducibility was explained by the low variation of F_EO₂ measurements, which had a CV of 0.9% (CI: 0.7-1.5%) combined with a slightly greater variability of F_ECO₂, V_E, VCO₂, and RER. In conclusion, the K5 is an excellent portable metabolic cart which is almost as accurate as a state-of-art stationary metabolic cart, capable of measuring precisely energy expenditure in the field, showing a reliable performance during more than 2 h of continuous work. At high intensities, the mixing-chamber mode is more accurate than the B×B mode.

Does the use of outdoor fitness equipment by older adults qualify as moderate to vigorous physical activity?

Despite the rapid worldwide expansion of parks with outdoor fitness equipment (OFE), no objective data regarding the intensity of activity associated with using OFE are available. Hence, this study quantified the energy expenditure and intensity of physical activity by examining four outdoor fitness devices widely used by older adults and provides objective evidence-based intensity references for the Compendium of Physical Activities. Sixteen older adults (mean age: 70.7 ± 5.6 yr) equipped with a portable metabolic system for measuring energy expenditure and activity intensity completed tasks while walking or using four types of OFE. Descriptive statistics and repeated-measures ANOVA with the Bonferroni post hoc test were employed. The energy expenditure and activity intensity for using an air walker at tempos of 80, 100, and 120 bpm were 50.78 ± 14.76 (2.81 ± 0.85), 59.62 ± 14.23 (3.26 ± 0.82), and 65.62 ± 18.27 (3.55 ± 1.02) cal/kg/min (METs), respectively. The induced energy and intensity output values for a ski machine were 54.00 ± 14.31 (3.02 ± 0.87), 68.87 ± 22.74 (3.82 ± 1.35), and 74.55 ± 23.39 (4.05 ± 1.35) cal/kg/min (METs), at 80, 100, and 120 bpm, respectively. The energy output for a waist twister at 60 bpm was 38.43 ± 20.16 cal/kg/min (2.05 ± 1.15 METs), and that for a double arm stretch at 80 bpm was 31.05 ± 12.58 cal/kg/min (1.63 ± 0.70 METs). These findings indicate that activity on the ski machine and air walker could be considered to have moderate intensity, whereas the intensity of activity on the waist twister and double arm stretch was significantly lower than that for walking at either 3.2 km/h or 4 km/h and could be considered only light intensity. The MET values for the OFE were lower than those for similar indoor fitness equipment. The results of this study provide crucial implications for public health practices concerning the development of active living environments.

Cardiorespiratory demand and rate of perceived exertion during overground walking with a robotic exoskeleton in long-term manual wheelchair users with chronic spinal cord injury: A cross-sectional study

BACKGROUND

Many wheelchair users adopt a sedentary lifestyle, which results in progressive physical deconditioning with increased risk of musculoskeletal, cardiovascular and endocrine/metabolic morbidity and mortality. Engaging in a walking program with an overground robotic exoskeleton may be an effective strategy for mitigating these potential negative health consequences and optimizing fitness in this population. However, additional research is warranted to inform the development of adapted physical activity programs incorporating this technology.

OBJECTIVES

To determine cardiorespiratory demands during sitting, standing and overground walking with a robotic exoskeleton and to verify whether such overground walking results in at least moderate-intensity physical exercise.

METHODS

We enrolled 13 long-term wheelchair users with complete motor spinal cord injury in a walking program with an overground robotic exoskeleton. Cardiorespiratory measures and rate of perceived exertion (RPE) were recorded by using a portable gas analyzer system during sitting, standing and four 10m walking tasks with the robotic exoskeleton. Each participant also performed an arm crank ergometer test to determine maximal cardiorespiratory ability (i.e., peak heart rate and O₂ uptake [HR_peak, VO_2peak]).

RESULTS

Cardiorespiratory measures increased by a range of 9%-35% from sitting to standing and further increased by 22%-52% from standing to walking with the robotic exoskeleton. During walking, median oxygen cost (O_2Walking), relative HR (%HR_peak), relative O₂ consumption (%VO_2peak) and respiratory exchange ratio (RER) reached 0.29mL/kg/m, 82.9%, 41.8% and 0.9, respectively, whereas median RPE reached 3.2/10. O_2Walking was moderately influenced by total number of sessions and steps taken with the robotic exoskeleton since the start of the walking program.

CONCLUSION

Overground walking with the robotic exoskeleton over a short distance allowed wheelchair users to achieve a moderate-intensity level of exercise. Hence, an overground locomotor training program with a robotic exoskeleton may have cardiorespiratory health benefits in the population studied.

RAAAF's office landscape The End of Sitting: Energy expenditure and temporary comfort when working in non-sitting postures

An earlier study suggested that the activity-inviting office landscape called “The End of Sitting”, designed by Rietveld Architecture Art Affordances (RAAAF), should be considered as an alternative working environment to prevent sedentary behavior. The End of Sitting lacks chairs and tables but consists instead of a myriad of sloped surfaces at different heights that afford workers to stand, lean or recline at different locations. In this study, we assessed the impact of four of its workspaces on physical intensity, temporary comfort and productivity of office work and compared the outcomes with sitting and standing behind a desk. Twenty-four participants worked for 10 minutes in each of the six test conditions. Energy expenditure, measured by indirect calorimetry, and heart rate were recorded. Questionnaires were used to assess the perceived comfort. The number of words found in the word search test was counted as a measure of productivity. The majority of The End of Sitting workspaces led to a significant increase in energy expenditure compared with sitting behind a desk (ps < .05). Average MET values ranged from 1.40 to 1.58 which is a modest rise in energy expenditure compared to sitting (1.32 METs) and not significantly different from standing (1.47 METs). The scores on the general comfort scale indicated that some workspaces were less comfortable than sitting (ps < .05), but the vast majority of participants reported that at least one of The End of Sitting workspaces was equally or more comfortable than sitting. No differences in productivity between the test conditions were found. Further long-term studies are required to assess the behavioral adaptations, productivity and the level of comfort when using The End of Sitting as a permanent office.

Reproducibility of the Internal Load and Performance-Based Responses to Simulated Amateur Boxing

Thomson, ED and Lamb, KL. Reproducibility of the internal load and performance-based responses to simulated amateur boxing. J Strength Cond Res 31(12): 3396-3402, 2017-The aim of this study was to examine the reproducibility of the internal load and performance-based responses to repeated bouts of a three-round amateur boxing simulation protocol (boxing conditioning and fitness test [BOXFIT]). Twenty-eight amateur boxers completed 2 familiarization trials before performing 2 complete trials of the BOXFIT, separated by 4-7 days. To characterize the internal load, mean (HRmean) and peak (HRpeak) heart rate, breath-by-breath oxygen uptake (V[Combining Dot Above]O2), aerobic energy expenditure, excess carbon dioxide production (CO2excess), and ratings of perceived exertion were recorded throughout each round, and blood lactate determined post-BOXFIT. Additionally, an indication of the performance-based demands of the BOXFIT was provided by a measure of acceleration of the punches thrown in each round. Analyses revealed there were no significant differences (p > 0.05) between repeated trials in any round for all dependent measures. The typical error (coefficient variation %) for all but 1 marker of internal load (CO2excess) was 1.2-16.5% and reflected a consistency that was sufficient for the detection of moderate changes in variables owing to an intervention. The reproducibility of the punch accelerations was high (coefficient of variance % range = 2.1-2.7%). In general, these findings suggest that the internal load and performance-based efforts recorded during the BOXFIT are reproducible and, thereby, offer practitioners a method by which meaningful changes impacting on performance could be identified.

Predicting metabolic rate during level and uphill outdoor walking using a low-cost GPS receiver

The objective of this study was to assess the accuracy of using speed and grade data obtained from a low-cost global positioning system (GPS) receiver to estimate metabolic rate (MR) during level and uphill outdoor walking. Thirty young, healthy adults performed randomized outdoor walking for 6-min periods at 2.0, 3.5, and 5.0 km/h and on three different grades: 1) level walking, 2) uphill walking on a 3.7% mean grade, and 3) uphill walking on a 10.8% mean grade. The reference MR [metabolic equivalents (METs) and oxygen uptake (V̇o2)] values were obtained using a portable metabolic system. The speed and grade were obtained using a low-cost GPS receiver (1-Hz recording). The GPS grade (Δ altitude/distance walked) was calculated using both uncorrected GPS altitude data and GPS altitude data corrected with map projection software. The accuracy of predictions using reference speed and grade (actual[SPEED/GRADE]) data was high [R(2) = 0.85, root-mean-square error (RMSE) = 0.68 MET]. The accuracy decreased when GPS speed and uncorrected grade (GPS[UNCORRECTED]) data were used, although it remained substantial (R(2) = 0.66, RMSE = 1.00 MET). The accuracy was greatly improved when the GPS speed and corrected grade (GPS[CORRECTED]) data were used (R(2) = 0.82, RMSE = 0.79 MET). Published predictive equations for walking MR were also cross-validated using actual or GPS speed and grade data when appropriate. The prediction accuracy was very close when either actual[SPEED/GRADE] values or GPS[CORRECTED] values (for level and uphill combined) or GPS speed values (for level walking only) were used. These results offer promising research and clinical applications related to the assessment of energy expenditure during free-living walking.

Comparison of the influence of age on cycling efficiency and the energy cost of running in well-trained triathletes

INTRODUCTION

Locomotive efficiency is cited as an important component to endurance performance; however, inconsistent observations of age-related changes in efficiency question its influence in the performance of masters athletes.

PURPOSE

This study examined locomotive efficiency in young and masters triathletes during both a run and cycle test.

METHODS

Twenty young (28.5 ± 2.6 years) and 20 masters (59.8 ± 1.3 years) triathletes completed an incremental cycling and running test to determine maximal aerobic consumption (VO2max) and the first ventilatory threshold (VT1). Participants then completed 10-min submaximal running and cycling tests at VT1 during which locomotive efficiency was calculated from expired ventilation. Additionally, body fat percentage was determined using skin-fold assessment.

RESULTS

During the cycle and run, VO2max was lower in the masters (48.3 ± 5.4 and 49.6 ± 4.8 ml kg(-1) min(-1), respectively) compared with young (61.6 ± 5.7 and 62.4 ± 5.2 ml kg(-1) min(-1), respectively) cohort. Maximal running speed and the cycling power output corresponding to VO2max were also lower in the masters (15.1 ± 0.8 km h(-1) and 318.6 ± 26.0 W) compared with the young (19.5 ± 1.3 km h(-1) and 383.6 ± 35.0 W) cohort. Cycling efficiency was lower (-11.2%) in the masters compared with young cohort. Similar results were observed for the energy cost of running (+10.8%); however, when scaled to lean body mass, changes were more pronounced during the run (+22.1%).

CONCLUSIONS

Within trained triathletes, ageing can influence efficiency in both the run and cycle discipline. While disregarded in the past, efficiency should be considered in research examining performance in ageing athletes.

Aerobic Capacity, Activity Levels and Daily Energy Expenditure in Male and Female Adolescents of the Kenyan Nandi Sub-Group

The relative importance of genetic and socio-cultural influences contributing to the success of east Africans in endurance athletics remains unknown in part because the pre-training phenotype of this population remains incompletely assessed. Here cardiopulmonary fitness, physical activity levels, distance travelled to school and daily energy expenditure in 15 habitually active male (13.9±1.6 years) and 15 habitually active female (13.9±1.2) adolescents from a rural Nandi primary school are assessed. Aerobic capacity ([Formula: see text]) was evaluated during two maximal discontinuous incremental exercise tests; physical activity using accelerometry combined with a global positioning system; and energy expenditure using the doubly labelled water method. The [Formula: see text] of the male and female adolescents were 73.9±5.7 ml(.) kg(-1.) min(-1) and 61.5±6.3 ml(.) kg(-1.) min(-1), respectively. Total time spent in sedentary, light, moderate and vigorous physical activities per day was 406±63 min (50% of total monitored time), 244±56 min (30%), 75±18 min (9%) and 82±30 min (10%). Average total daily distance travelled to and from school was 7.5±3.0 km (0.8-13.4 km). Mean daily energy expenditure, activity-induced energy expenditure and physical activity level was 12.2±3.4 MJ(.) day(-1), 5.4±3.0 MJ(.) day(-1) and 2.2±0.6. 70.6% of the variation in [Formula: see text] was explained by sex (partial R(2) = 54.7%) and body mass index (partial R(2) = 15.9%). Energy expenditure and physical activity variables did not predict variation in [Formula: see text] once sex had been accounted for. The highly active and energy-demanding lifestyle of rural Kenyan adolescents may account for their exceptional aerobic fitness and collectively prime them for later training and athletic success.