Biologically inspired evolutionary computing tools for the extraction of fetal electrocardiogram

Authors:
Ravi Kumar Jatoth;Saladi S. V. K. K. Anoop;Ch. Midhun Prabhu
Affiliations:
Department of Electronics and Communication Engineering, National Institute of Technology Warangal, Warangal, India;Department of Electronics and Communication Engineering, National Institute of Technology Warangal, Warangal, India;Department of Electronics and Communication Engineering, National Institute of Technology Warangal, Warangal, India
Venue:
WSEAS Transactions on Signal Processing
Year:
2009

Citing 5
Cited 0

Adaptive signal processing

Adaptive signal processing
Adaptive filter theory (2nd ed.)

Adaptive filter theory (2nd ed.)
Bioinformatics: the machine learning approach

Bioinformatics: the machine learning approach
Parametrical modelling of a premature ventricular contraction ECG beat: Comparison with the normal case

Computers in Biology and Medicine
Detecting acute myocardial infarction in the 12-lead ECG using Hermite expansions and neural networks

Artificial Intelligence in Medicine

Quantified Score

Hi-index	0.00

Visualization

Abstract

Signals recorded from the human body provide valuable information about the biological activities of body organs. The spectral properties of different organs help in medical diagnosis. Even small changes in functioning of organs is indicated by the changes in their spectra. Fetal heart rate extraction from the abdominal ECG is of great importance because the information carried by it is helpful in assessing appropriately the fetus well-being during pregnancy. Fetal ECG is always contaminated by a drift and interference caused by several bioelectric phenomena, or by various types of noise, such as intrinsic noise from the recorder and noise from electrode-skin contact. The low Signal to noise Ratio of fetal ECG makes it difficult to analyze it effectively. Accurate detection of QRS complex is a pre-requisite in the assessment of fetal heart beat. In this paper we utilize an intelligent Adaptive Filter for noise cancellation in the effective extraction and analysis of fetal ECG. The PSO based adaptive noise cancellation technique is shown to be superior to the conventional FIR adaptive filtering.