monitoring the user during the physical activity with the wearable electronic device, the wearable electronic device including a photoplethysmography (PPG) sensor to detect changes in blood volume of the user during the physical activity, an accelerometer to capture acceleration of the user during the physical activity, a memory to store demographic data of the user, data from the PPG sensor and data from the accelerometer and a processor to process the data obtained from the PPG sensor and the data from the accelerometer;

computing, using the data from the PPG sensor and the data from the accelerometer, a PPG heart rate estimate and a PPG quality flag;

computing an exponential heart rate estimate by applying the PPG heart rate estimate, the PPG quality flag and the demographic data of the user in an exponential approximation model;

the exponential approximation model being determined by:

where, HR (t+1) is the exponential estimate of heart rate,

is a parameter that indicates an increase or decrease in that heart rate calculated in a previous iteration, and T is a constant that determines the increase or decrease in rate,

where, is determined by:

where D_s is a matrix that defines [AL, BMI, age, male, female], AL is a normalized raw activity level, BMI is a body mass index and male or female assumes 1 or 0, the parameter determined according to intensity of the physical activity of the user and W^T is transposition of a matrix of weights that affect behavior of the exponential approximation model;

outputting, provided the PPG quality flag indicates that the data captured from the PPG sensor is reliable, the PPG heart rate estimate; and

outputting, provided the PPG quality flag indicates that the data captured from the PPG sensor is unreliable, the exponential heart rate estimate.