CardioGen Simulator

CardioGen Simulator is a hierarchical generative model for cardiological signals (PPG,ECG etc.) that keeps the physiological characteristics intact.

This deep generative model comprises of two W-GAN’s, one inside each of HR2Rpeaks_Simulator and Rpeaks2EcgPpg_Simulator objects. Both of these are conditional generative models which incrementally add desired marginal information over the given conditional information.

How it works.

HR2Rpeaks_Simulator takes smooth Heart Rate (HR) averaged over a sliding window of 8s. and low-pass filtered along-with subject class as input condition and generates an R-peak train at Fs_out=100Hz with 1’s at R-peak locations and 0’s everywhere else. Internally, the W-GAN models uniformly-spaced tachograms at 5 Hz. Hence, HR2Rpeaks_Simulator adds subject-specific Heart Rate Variability (HRV) information to the input HR.

Rpeaks2EcgPpg_Simulator takes the R-peak train at Fs_in=100Hz. along-with subject class as input condition and generates an ECG signal at Fs_out=100Hz. Hence, Rpeaks2EcgPpg_Simulator adds subject-specific Morphological (Morph) information to the input R-peak train.

Currently, the W-GAN in HR2Rpeaks_Simulator has a single set of weights while the W-GAN in Rpeaks2EcgPpg_Simulator has subject specific fine-tuned weights.