Extension of FRI for modeling of electrocardiogram signals

Abstract

Abstract-Recent work has developed a modeling method applicable to certain types of signals having a "finite rate of innovation" (FRI). Such signals contain a sparse collection of time-or frequency-limited pulses having a restricted set of allowable pulse shapes. A limitation of past work on FRI is that all of the pulses must have the same shape. Many real signals, including electrocardiograms, consist of pulses with varying widths and asymmetry, and therefore are not well fit by the past FRI methods. We present an extension of FRI allowing pulses having variable pulse width (VPW) and asymmetry. We show example results for electrocardiograms and discuss the possibility of application to signal compression and diagnostics.

Fetal heart rate detection using VPW-FRI

“…Only a summary of the VPW-FRI method in [7] will be shown here for the sake of brevity and extensive discussions can be found in [2,3,7]. The VPW-FRI is an extension of the FRI sampling and reconstruction scheme which was designed for a certain class of parametric signals which are not bandlimited.…”

“…The pulse model allows VPW-FRI to model signals as a sum of pulses which can be compressed by calculating the four parameters associated with each pulse. For example in regular ECG [2,3] it has been shown that a single heartbeat with, various morphologies, can be modelled using seven pulses giving 28 parameters. Depending on the HR, this can lead to substantial compression subject to the sampling rate of the data.…”

“…The VPW-FRI algorithm [2,3,7] was chosen for this problem due to its ability to parameterize the fECG data and identify individual pulses associated with the fQRS. This is derived from VPW-FRI's Lorentzian pulse model which accounts for various widths and degrees of asymmetry.…”