Identification of Non-Invasive Exercise Thresholds: Methods, Strategies, and an Online App

呼吸补偿 医学 运动生理学 运动处方 资源(消歧) 计算机科学 乳酸阈 通气阈值 运动医学 鉴定(生物学) 血乳酸 物理疗法 无氧运动 最大VO2 内科学 心率 血压 生物 植物 计算机网络
作者
Daniel A. Keir,Danilo Iannetta,Felipe Mattioni Maturana,John M. Kowalchuk,Juan M. Murias
出处
期刊:Sports Medicine [Springer Science+Business Media]
卷期号:52 (2): 237-255 被引量:89
标识
DOI:10.1007/s40279-021-01581-z
摘要

During incremental exercise, two thresholds may be identified from standard gas exchange and ventilatory measurements. The first signifies the onset of blood lactate accumulation (the lactate threshold, LT) and the second the onset of metabolic acidosis (the respiratory compensation point, RCP). The ability to explain why these thresholds occur and how they are identified, non-invasively, from pulmonary gas exchange and ventilatory variables is fundamental to the field of exercise physiology and requisite to the understanding of core concepts including exercise intensity, assessment, prescription, and performance. This review is intended as a unique and comprehensive theoretical and practical resource for instructors, clinicians, researchers, lab technicians, and students at both undergraduate and graduate levels to facilitate the teaching, comprehension, and proper non-invasive identification of exercise thresholds. Specific objectives are to: (1) explain the underlying physiology that produces the LT and RCP; (2) introduce the classic non-invasive measurements by which these thresholds are identified by connecting variable profiles to underlying physiological behaviour; (3) discuss common issues that can obscure threshold detection and strategies to identify and mitigate these challenges; and (4) introduce an online resource to facilitate learning and standard practices. Specific examples of exercise gas exchange and ventilatory data are provided throughout to illustrate these concepts and a novel online application tool designed specifically to identify the estimated LT (θLT) and RCP is introduced. This application is a unique platform for learners to practice skills on real exercise data and for anyone to analyze incremental exercise data for the purpose of identifying θLT and RCP.
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