Methods and systems utilize combinations of gaseous concentration, contextual and location information provided by environmental sensors with physiological data provided by wearable sensors to personalize the parameters used in computational models for estimating metabolic parameters. This personalization allows for parameter estimates that better account for the subject-dependent nature of the relationship between heart rate and various metabolic features.
