The Ornstein-Uhlenbeck third-order Gaussian process (OUGP) applied directly to the un-resampled heart rate variability (HRV) tachogram for detrending and low-pass filtering

摘要

The heart rate variability signal derived from the ECG is a beat-to-beat record of RR-intervals and is, as a time series, irregularly sampled. It is common engineering practice to resample this record, typically at 4 Hz, onto a regular time axis for conventional analysis using IIR and FIR filters, and power spectral estimators, in the time and frequency domain, respectively. However, such interpolative resampling introduces noise into the signal and the information quality is compromised. Here, the Ornstein-Uhlenbeck third-order band-pass filter is presented which operates on data sampled at arbitrary time and preserves fidelity. The algorithm is available as open source code for MATLAB? (MathWorks? Inc.) and supported by an interactive website at http://clinengnhs.liv.ac.uk/OUGP.htm.