Lattice filters for time-variant processing of heart rate variability

Time-variant or adaptive methods for parametric spectral estimation have become of increasing interest for heart rate variability (HRV) signal-processing during nonstationary epochs. In this study a lattice filter is presented, which proceeds a time-variant estimation of nested autoregressive models...

Full description

Saved in:
Bibliographic Details
Main Authors: Sholz, Udo, Cerutti, Sergio
Format: Conference Proceeding
Language:English
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Time-variant or adaptive methods for parametric spectral estimation have become of increasing interest for heart rate variability (HRV) signal-processing during nonstationary epochs. In this study a lattice filter is presented, which proceeds a time-variant estimation of nested autoregressive models, allowing a successive order selection. The performance of this method exceeds the known fixed order algorithms regarding the spectral representation of the HRV signal, as obtained on simulations and on real data detected during sleep stages in normal subjects.