PT  - JOURNAL ARTICLE
AU  - M A Pacheco Pereira
AU  - R Almeida
AU  - H Dias
TI  - VO2 prediction based on physiologic and mechanical exercise measurements
AID  - 10.1183/13993003.congress-2022.4270
DP  - 2022 Sep 04
TA  - European Respiratory Journal
PG  - 4270
VI  - 60
IP  - suppl 66
4099  - http://erj.ersjournals.com/content/60/suppl_66/4270.short
4100  - http://erj.ersjournals.com/content/60/suppl_66/4270.full
SO  - Eur Respir J2022 Sep 04; 60
AB  - The Cardiopulmononary Exercise Test (CPET) is a diagnostic test that evaluates the functional capacity of na individual through the integrated response of the cardiovascular, respiratory and metabolic systems. VO2max is the parameter that acess functional capacity, although it’s difficult to achieve given the effort that implies.In recent years, an increase in computing capabilities combined with available storage of large amounts of information has led to a heightened interest in machine learning (ML).We aimed in this study to enable CPET with ML models that allow predicting oxygen consumption in healthy individuals.The study methodology is based on the cleaning and exploratory analysis of a public database with about 992 CPET performed on healthy individuals and athletes.To predict the each value of VO2 (~569,000 instances), five ML algorithms were used (Random Forests, kNN, Neural Networks, Linear Regression and SVM) with heart rate, respiratory rate, time from the beginning of the exame and treadmill speed, using a 20-fold cross-validation.The best result came from the Random Forest model, with a R2 of 0.88 and a RMSE of 334.34 ml.min-1.Futhermore, using the same methodology but different features, we tried to predict the the VO2max with the 724 adult participants with a maximal test (RER≥1.05) but weaker results were obtained (best model was the Linear Regression, with a R2 of 0.50 and a RMSE of 498.06 ml.min-1). Still, this model showed a better correlation with the real VO2max than the Wasserman equation (R=0.71 vs R=0.59).It’s possible to predict with accuracy breath-by-breath VO2, based in easy-to-obtain physiological and mechanical measurements.FootnotesCite this article as Eur Respir J 2022; 60: Suppl. 66, 4270.This article was presented at the 2022 ERS International Congress, in session “-”.This is an ERS International Congress abstract. No full-text version is available. Further material to accompany this abstract may be available at www.ers-education.org (ERS member access only).