The prediction of oxygen consumption during arm work ergometry

Abstract

The purpose of this study was to examine oxygen consumption (VO2) patterns during arm work ergometry and to determine if VO2 (ml kg‐1 min‐1) could be accurately predicted from workload and attribute variables. Thirty‐two male subjects were chosen to form a homogeneous group in regard to age, gender, and percentage body fat, but at the same time to produce a large range in body weight. Each subject performed a continuous exercise test on an arm ergometer to voluntary exhaustion. Oxygen consumption and heart rate were determined and averaged for each workload. Multiple linear regression with a forward solution was utilized in the primary analysis of the data; dependent variable, VO2 (ml kg‐1 min‐1). VO2 (1 min‐1) and VO2 (ml kg‐1 min‐1) increased throughout the workload range, being significantly greater for light than heavy subjects, particularly at high workloads. Workload, weight and the workload × weight product (workload × weight/100) added significantly to the prediction of VO2 (ml kg‐1 min‐1) when introduced into a forward solution, respectively. When the order of entry for weight and the workload x weight product was reversed, weight became unimportant as a predictor. It was concluded that the accurate prediction of VO2 (ml kg‐1 min‐1) during arm ergometry is possible and that workload, weight and their interaction should be considered in the development of a predictive model. The model which contained only the workload and the workload x weight product produced the best fit for these data.

Key Words:

• Arm ergometry
• oxygen consumption
• regression