An adaptive 'Wiener' filter for estimating the time-derivative of the left ventricular pressure signal

The development of an optimal digital differentiating filter based on the Wiener theory for estimating the peak derivative of the left ventricular pressure (LVP) signal is discussed. The magnitude coherence function is used to estimate the signal and noise spectra. The peak derivative obtained by th...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on biomedical engineering 1990-04, Vol.37 (4), p.417-420
Main Authors: Periyalwar, S., Marble, A.E., Nugent, S.T., Swingler, D.N.
Format: Article
Language:English
Subjects:
Adaptive filters
Additive noise
Algorithms
Biological and medical sciences
Cardiology. Vascular system
Digital filters
Frequency estimation
Heart
Humans
Medical sciences
Models, Cardiovascular
Muscles
Power harmonic filters
Pressure
Signal processing
Signal Processing, Computer-Assisted
Signal to noise ratio
Ventricular Function
Wiener filter
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The development of an optimal digital differentiating filter based on the Wiener theory for estimating the peak derivative of the left ventricular pressure (LVP) signal is discussed. The magnitude coherence function is used to estimate the signal and noise spectra. The peak derivative obtained by this method is found to be within 2% of the results obtained by a seven-point second-order data fit and a discrete Fourier transform technique.< >
ISSN:0018-9294
1558-2531
DOI:10.1109/10.52349