| abstract |
A method of generating a model for heart rate estimation from a photoplethysmography, PPG, signal of a subject comprises: receiving ( 102 ) subject-specific training data for machine learning, said training data comprising a PPG signal from the subject and a heart rate indicating signal from the subject, wherein the heart rate indicating signal provides a ground truth of heart rates of the subject for associating a heart rate with a time period of the PPG signal; using ( 104 ) associated pairs of a heart rate and a complete dataset of a time-series of a PPG signal over a time period as input to a deep neural network, DNN; and determining ( 106; 312 ), through the DNN, a subject-specific model relating the PPG signal of the subject to the heart rate of the subject. |