Meaningful dissociations between [Formula: see text]O2pulm and [Formula: see text]O2musc kinetics exist for both UpBody and LoBody exercise during rapid work rate changes. Therefore, isolated [Formula: see text]O2pulm kinetic estimations without the consideration of the circulatory distortions may not allow a reliable assessment of [Formula: see text]O2musc kinetics.

IntroductionIn the context of the COVID-19 pandemic in Germany, governmental restrictions led to the closure of sports facilities for several months. To date, only subjective and fitness-tracking related data on physical activity during the pandemic are available. Using data of a chip-controlled fitness circuit, training data as a measure of physical performance before and after the lockdown during the first wave of the COVID-19 pandemic will show the impact of the training interruption on exercise performance in middle-aged and older adults. The re-training data are analyzed, to extract practical recommendations.MethodsObjective training data of 17,450 participants [11,097 middle-aged (45–64 yrs), 6,353 older (≥65 yrs)] were exported from chip-controlled milon® fitness circuit systems before and after the first COVID-19 related lockdown in Germany. The change in the product of training weight (sum of lifting and lowering the training weight) and repetitions on the leg extension resistance exercise device (leg score) between the last three training sessions before the lockdown and the first ten training sessions after individual training resumption as well as the last training session before the second lockdown in October 2020 was analyzed.ResultsParticipants who trained with high intensity before the lockdown, experienced deleterious effects of the training interruption (middle-aged group: −218 kg, older group: ~−230.8 kg; p < 0.001 for change in leg score from to post-lockdown) with no age effect. Participants training with a leg score of more than 3,000 kg did not resume their leg score until the second lockdown.ConclusionThe interruption of training in a fitness circuit with combined resistance and endurance training due to the lockdown affected mainly those participants who trained at high intensity. Apparently, high-intensity training could not be compensated by home-based training or outdoor activities. Concepts for high-intensity resistance training during closure of sports facilities are needed to be prepared for future periods of high incidence rates of infectious diseases, while especially vulnerable people feel uncomfortable to visit sports facilities.Trial registrationIdentifier, DRKS00022433.

No abstract

Despite hemodynamic changes, [Formula: see text]O kinetics seem to be preserved for a longer period of HDBR, even without the application of a countermeasure.

This study aims to compare cardiorespiratory kinetics as a response to a standardised work rate protocol with pseudo-random binary sequences between cycling and walking in young healthy subjects. Muscular and pulmonary oxygen uptake (V̇O) kinetics as well as heart rate kinetics were expected to be similar for walking and cycling. Cardiac data and V̇O of 23 healthy young subjects were measured in response to pseudo-random binary sequences. Kinetics were assessed applying time series analysis. Higher maxima of cross-correlation functions between work rate and the respective parameter indicate faster kinetics responses. Muscular V̇O kinetics were estimated from heart rate and pulmonary V̇O using a circulatory model. Muscular (walking vs. cycling [mean±SD in arbitrary units]: 0.40±0.08 vs. 0.41±0.08) and pulmonary V̇O kinetics (0.35±0.06 vs. 0.35±0.06) were not different, although the time courses of the cross-correlation functions of pulmonary V̇O showed unexpected biphasic responses. Heart rate kinetics (0.50±0.14 vs. 0.40±0.14; P=0.017) was faster for walking. Regarding the biphasic cross-correlation functions of pulmonary V̇O during walking, the assessment of muscular V̇O kinetics via pseudo-random binary sequences requires a circulatory model to account for cardio-dynamic distortions. Faster heart rate kinetics for walking should be considered by comparing results from cycle and treadmill ergometry.

New Findings What is the central question of this study?Breath‐by‐breath gas exchange analysis during treadmill exercise can be disturbed by different breathing patterns depending on cadence, and the flow sensor might be subjected to variable mechanical stress. It is still unclear whether the outcomes of the gas exchange algorithms can be affected by running at different speeds. What is the main finding and its importance?Practically, the three investigated breath‐by‐breath algorithms (‘Wessel’, ‘expiration‐only’ and ‘independent breath’) provided similar average gas exchange values for steady‐state conditions. The ‘independent breath’ algorithm showed the lowest breath‐by‐breath fluctuations in the gas exchange data compared with the other investigated algorithms, both at steady state and during incremental exercise. Abstract Recently, a new breath‐by‐breath gas exchange calculation algorithm (called ‘independent breath’) was proposed. In the present work, we aimed to compare the breath‐by‐breath O2 uptake (V̇normalO2) values assessed in healthy subjects undergoing a running protocol, as calculated applying the ‘independent breath’ algorithm or two other commonly used algorithms. The traces of respiratory flow, O2 and CO2 fractions, used by the calculation algorithms, were acquired at the mouth on 17 volunteers at rest, during running on a treadmill at 6.5 and 9.5 km h−1, and thereafter up to volitional fatigue. Within‐subject averages and standard deviations of breath‐by‐breath V̇normalO2 were calculated for steady‐state conditions; the V̇normalO2 data of the incremental phase were analysed by means of linear regression, and their root mean square was assumed to be an index of the breath‐by‐breath fluctuations. The average values obtained with the different algorithms were significantly different (P < 0.001); nevertheless, from a practical point of view the difference could be considered ‘small’ in all the investigated conditions (effect size <0.3). The standard deviations were significantly lower for the ‘independent breath’ algorithm (post hoc contrasts, P < 0.001), and the slopes of the relationships with the corresponding data yielded by the other algorithms were <0.70. The root mean squares of the linear regressions calculated for the incremental phase were also significantly lower for the ‘independent breath’ algorithm, and the slopes of the regression lines with the corresponding values obtained with the other algorithms were <0.84. In conclusion, the ‘independent breath’ algorithm yielded the least breath‐by‐breath O2 uptake fluctuation, both during steady‐state exercise and during incremental running.

No abstract

Efforts to better understand cardiorespiratory health are relevant for the future development of optimized physical activity programs. We aimed to explore the impact of the signal quality on the expected associations between the ability of the aerobic system in supplying energy as fast as possible during moderate exercise transitions with its maximum capacity to supply energy during maximal exertion. It was hypothesized that a slower aerobic system response during moderate exercise transitions is associated with a lower maximal aerobic power; however, this relationship relies on the quality of the oxygen uptake dataset. Forty-three apparently healthy participants performed a moderate constant work rate (CWR) followed by a pseudorandom binary sequence (PRBS) exercise protocol on a cycle ergometer. Participants also performed a maximum incremental cardiopulmonary exercise testing (CPET). The maximal aerobic power was evaluated by the peak oxygen uptake during the CPET and the aerobic fitness was estimated from different approaches for oxygen uptake dynamics analysis during the CWR and PRBS protocols at different levels of signal-to-noise ratio. The product moment correlation coefficient was used to evaluate the correlation level between variables. Aerobic fitness was correlated with maximum aerobic power, but this correlation increased as a function of the signal-to-noise ratio. Aerobic fitness is related to maximal aerobic power; however, this association appeared to be highly dependent on the data quality and analysis for aerobic fitness evaluation. Our results show that simpler moderate exercise protocols might be as good as maximal exertion exercise protocols to obtain indexes related to cardiorespiratory health.