Prediction of oxygen uptake kinetics during heavy-intensity cycling exercise by machine learning analysis
Eric T. Hedge, Robert Amelard, Richard L. Hughson
Abstract
Machine learning analysis of wearable sensor data with a sequential model, which utilized a receptive field of approximately 3 min to make instantaneous oxygen uptake estimations, accurately predicted oxygen uptake kinetics from moderate through to higher-intensity exercise. This innovation will enable nonintrusive cardiorespiratory monitoring over a wide range of exercise intensities encountered in vigorous training and competitive sports.
Topics & Concepts
CyclingCardiorespiratory fitnessIntensity (physics)OxygenKineticsVO2 maxExercise intensityEnvironmental scienceSimulationChemistryComputer sciencePhysical therapyHeart rateMedicinePhysicsInternal medicineOrganic chemistryHistoryQuantum mechanicsArchaeologyBlood pressureCardiovascular and exercise physiologySports Performance and TrainingCardiovascular Effects of Exercise