The current invention pertains to a method whereby the accuracy of a heart rate prediction gathered from sensor data can be improved during periods when motion corrupts the signal. The model utilized can also be inverted to infer information on the physiological state of a subject, such as real-time energy utilization or physiological load. In addition, this method can also be used to segment the contribution of each energy system, namely the phosphagen system, anaerobic glycolysis and aerobic respiration, to the physiological load experienced by the user. At the core of this approach lies a model describing the dynamic adjustment of human heart rate under varying physiological demands.
