Study aim: Oxygen Uptake (VO2) is avaluable metric for the prescription of exercise intensity and the monitoring of training progress.However, VO2 is difficult to assess in anon-laboratory setting.Recently, an artificial neural network (ANN) was used Swimming Goggles to predict VO2 responses during aset walking protocol on the treadmill [9].
The purpose of the present study was to test Shovels the ability of an ANN to predict VO2 responses during cycling at self-selected intensities using Heart Rate (HR), time derivative of HR, power output, cadence, and body mass data.