Artificial neural networks for aerobic fitness approximation
K. Vainamo, Seppo Nissilä, T. Makikalio, Mikko Paavo Tulppo, Juha Röning · 2002
A unique method for approximating aerobic fitness from demographic and heart rate variables using an artificial neural network (ANN) approximation is proposed. Conventional oxygen uptake measurement methods are expensive and require special clinical instruments. The present method is based on a structure of two ANNs connected in a serial fashion. The first ANN structure is called a preclassifier. It has inputs of physiological features and fuzzy features identified in the material used. The latter ANN structure is a primary approximator, which has an input of the preclassifier result and certain statistical features calculated from the heart rate recordings.