An preliminary Study on Applying Nonlinear Noise Reduction in the Analysis of HRV

摘要

This article proposes an enhancement of these HRV components through the application of a noise-reduction method in state space. The method works directly in an embedding space and corrects noisy trajectories, projecting them onto local subspaces that are a good approximation of the original surface of the system attractor. At any iteration, the procedure returns a new time series with the relevant amount of subtracted noise. An empiric criterion, originally proposed estimates the optimum iteration number to reach a good result in terms of signal-to noise ratio. Ultimately, our goal is to verify a possible improvement of the diagnostic and prognostic power of HRV analysis through the use of new nonlinear approaches that appear as a promising tool in the early identification of dangerous cardiovascular events.