Within and between-day reliability of energetic cost measures during treadmill walking. Issue 1 (31st December 2016)

• Record Type: Journal Article
• Authors: Davidson, Audra; Gardinier, Emily S.; Gates, Deanna H.
• Editors: Jin, Zhongmin
• Is Part Of: Cogent engineering. Volume 3:Issue 1(2016)
• Publication Date: 2016-12-31
• Subjects: reliability -- gait -- energetics -- metabolic cost -- assistive walking devices; Engineering -- Periodicals; Technology -- Periodicals; Engineering; Technology; Periodicals; 620
• DOI: 10.1080/23311916.2016.1251028
• Languages: English
• ISSNs: 2331-1916

Abstract

Abstract: The efficacy of assistive devices used during walking is often measured as a reduction in metabolic cost. Metabolic cost is typically assessed within a day or on multiple days, yet the benefit of performing within-day vs. between-day metabolic assessments is unknown. The purpose of this study was to determine the within-day minimal detectable change of standard measures of physiologic performance using a conventional portable metabolic system (K4b 2 Cosmed, Rome, Italy), and compare these to between-day values. Twenty healthy adults completed two identical data collection sessions on separate days. In each session they performed three bouts of treadmill walking interspersed with three bouts of rest while oxygen consumption (V O 2 ˙ ), carbon dioxide production, and heart rate were measured. Intraclass correlation coefficients (ICC) and minimal detectable change values were calculated for non-resting within-day, as well as all between-day comparisons. All within-day measures were clinically reliable (ICC > 0.96), while between-day measures were generally less reliable (ICCs > 0.82). Within-day minimal detectable change values (walking heart rate = 4.9 bpm; gross V O 2 ˙ = 0.80 mL/kg/min; net V O 2 ˙ = 0.80 mL/kg/min; cost of transport = 0.022 J/Nm) were about half as large as between-day values. The results of this study suggest that, where possible, physiologic changes should be assessed within a single day of testing to maximize ability to detect small changes in performance.