Predicting oxygen uptake responses during cycling at varied intensities using an artificial neural network

Predicting oxygen uptake responses during cycling at varied intensities using an artificial neural network

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Study aim: Oxygen Uptake (VO2) is avaluable metric for the prescription of exercise intensity and the monitoring of training progress.However, VO2 is difficult keychron m4 to assess in anon-laboratory setting.Recently, an artificial neural network (ANN) was used to predict VO2 responses during aset walking protocol on the treadmill [9].The purpose of the present study operation igloo white was to test 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.