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Breath‐by‐breath oxygen uptake during running: Effects of different calculation algorithms

机译:运行过程中呼吸呼吸氧气摄取:不同计算算法的影响

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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 O 2 uptake ( V ? O 2 ) 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, O 2 and CO 2 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 V ? O 2 were calculated for steady‐state conditions; the V ? O 2 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 O 2 uptake fluctuation, both during steady‐state exercise and during incremental running.
机译:新发现这项研究的核心问题是什么?根据节奏的不同呼吸模式,跑步机锻炼期间的呼吸气体交换分析可以受到不同的呼吸模式,并且流量传感器可能会受到可变的机械应力。目前还不清楚气体交换算法的结果是否可以以不同的速度运行来影响。主要发现和重要性是什么?实际上,三个调查的呼吸逐呼吸算法('Wessel',仅限“和”独立呼吸“)为稳态条件提供了类似的平均气体交换价值。与稳态和增量运动期间的其他研究算法相比,“独立呼气”算法显示了气体交换数据中的最低呼吸波动。摘要最近,提出了一种新的呼吸气体交换计算算法(称为“独立呼吸”)。在目前的工作中,我们旨在比较在正在进行运行协议的健康受试者中评估的呼吸逐呼吸o 2摄取(v?o 2)值,如计算应用'独立呼吸'算法或另外两个常用算法。计算算法使用的呼吸流量,O 2和Co 2分数的痕量,在休息的17个志愿者上,在跑步机上在6.5和9.5的跑步机上进行,然后达到无与伦比的疲劳。呼吸呼吸v的主题平均值和标准偏差v? o 2针对稳态条件计算; v?通过线性回归分析增量相的2数据,并且假设其根均线是呼吸呼吸波动的指标。用不同算法获得的平均值显着不同(P≤≤0.001);然而,从实际的角度来看,在所有研究条件下,差异可能被认为是“小”(效果大小?<0.3)。 “独立呼气”算法(后HOC对比度,P≤0.001),标准偏差显着降低,并且与其他算法产生的相应数据的关系的斜率为<0.70。对于“独立呼气”算法,为增量相计算的线性回归的根平均正方形也显着降低,并且具有与其他算法获得的相应值的回归线的斜率Δ<0.84。总之,“独立呼气”算法产生稳态运动期间和增量运行期间的逐呼吸逐呼吸的呼吸波动。

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