Monitoring the respiratory rate (RR) is important in many clinical and non-clinical situations but it is difficult in practice, for existing devices are obtrusive, bulky and expensive. The extraction of the RR from the routinely acquired electrocardiogram (ECG) has been proposed lately. Two approaches exist, one exploiting the modulation of the heart rate by the respiration, known as the respiratory sinus arrhythmia (RSA) and the other using the modulation by the respiration of the R-peak amplitudes (RPA). In this study, the weighted multi-signal oscillator based band pass filtering (W-OSC) algorithm is applied to track the common frequency in the RSA and RPA waveforms simultaneously, as an estimate of the instantaneous RR. On the public PhysioNet Fantasia data set, it is shown that the presented method is automatic, instantaneous and comparable in accuracy to the state-of-the-art. autoregressive band-pass filter breaths per minute electrocardiogram empirical mode decomposition error percentage intrinsic mode function mean absolute error oscillator based band-pass filtering R-peak amplitude respiratory rate respiratory sinus arrhythmia short time Fourier transform weighted multi-signal oscillator based band-pass filtering 
Respiratory rate estimation from the ECG using an instantaneous frequency tracking algorithm