Time-varying threshold integral pulse frequency modulation

Several methods have been proposed so far for the analysis of the integral pulse frequency modulation (IPFM) model and detecting its corresponding phy siological information. Most of these methods rely on the low-pass filterin g method to extract the modulating signal of the model. In this paper, we p resent an entirely new approach based on vector space theory. The new metho d is developed for a more comprehensive form of the IPFM model, namely the time-varying threshold integral pulse frequency modulation (TVTIPFM) model. The new method decomposes the driving signals of the TVTIPFM model into a series of orthogonal basis functions and constructs a matrix identity throu gh which the input signals can be obtained by a parametric solution. As a p articular case, we apply this method to R-R intervals of the SA node to dis criminate between its autonomic nervous modulation and the stretch induced effect.