Samsung Eletronica Da Amazonia Ltda.

Marcus De Assis Angeloni

Dong Hyun Lee

In Taek Oh

Ciro Cavani

Antonio Joia Neto

A method for predicting maximal oxygen uptake (VOMax) in wearable devices with memory restriction using an ensemble of machine learning algorithms is described. The method is related to the fields of well-being, healthcare and artificial intelligence, and includes a technique that predicts maximal oxygen uptake (VOMax) in running sessions at different paces using wearable devices with memory restriction. The proposed method requires less than 5 KB of memory to run on a wearable device. Specifically, based on user's profile data (age, gender, height and weight), a set of heart rate (HR) and speed readings of a running session, the method is able to estimate VOMax.

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Campinas—São Paulo, Brazil

Marcus De Assis Angeloni