Suppr超能文献

具有高时间分辨率的气体交换测量:逐次呼吸法。

Gas exchange measurements with high temporal resolution: the breath-by-breath approach.

作者信息

Roecker K, Prettin S, Sorichter S

机构信息

University of Freiburg, Medical Clinic and Polyclinic, Department of Sports Medicine, Freiburg, Germany.

出版信息

Int J Sports Med. 2005 Feb;26 Suppl 1:S11-8. doi: 10.1055/s-2004-830506.

Abstract

Respiratory gas analysis as an indicator for metabolic strain during exercise has a long history. First introduced in the 18th century, huge gas collectors served for the determination of oxidative energy delivery. While still being accepted as accurate, this particular method delivers data of low temporal resolution only. Further developments of gas analysis techniques therefore focused on a higher density of data. When algorithms became available for indispensable calculations, the so-called "breath-by-breath" (BBB) method was established some decades ago. Thereby, the term BBB in the narrower sense means that a particular physiologic value is determined for each of a subject's single respiratory cycles. Reliable application of this approach depends on the performance of available computer systems, the quality of the analyzing software routines, and the responsiveness of the gas analyzers. Thus, it appears that even nowadays technical progress is continuing in this area. This review describes technical aspects and prerequisites of the BBB approach and its specific areas of application.

摘要

将呼吸气体分析作为运动期间代谢应激的指标已有很长历史。该方法于18世纪首次引入,当时巨大的气体收集器用于测定氧化能量供应。虽然这种特定方法仍被认为是准确的,但它只能提供时间分辨率较低的数据。因此,气体分析技术的进一步发展集中在更高的数据密度上。当算法可用于进行必不可少的计算时,几十年前建立了所谓的“逐次呼吸”(BBB)方法。从狭义上讲,BBB一词意味着为受试者的每个单一呼吸周期确定一个特定的生理值。这种方法的可靠应用取决于现有计算机系统的性能、分析软件程序的质量以及气体分析仪的响应能力。因此,即使在当今,这一领域的技术进步仍在继续。本综述描述了BBB方法的技术方面、先决条件及其特定应用领域。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验