Secondary wavelet feature decoupling (SWFD) and its use in detecting patient respiration from the photoplethysmogram

We describe a method for the identification of time-frequency features associated with patient respiration in the wavelet decomposition of the photoplethysmogram where the respiration features are masked by other signal components with similar spectral content. In the novel methodology a secondary transform is performed on a signal derived from the original wavelet decomposition in the region of the pulse band. The method has wide application to many other problematic signals.