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Papers on Ventricular Fibrillation Algorithms

(1) Filtering of ECG signals, matlab file

(i) filtering.m

Description: The filtering algorithm works in four successive steps. First, the mean value of the signal is subtracted from the signal. Secondly, a moving averaging filter is applied in order to remove high frequency noise. Then, a drift suppression is carried out. This removes slow signal changes, which originate from external sources and are not produced by the heart. In a last step a butterworth filter with a cut off frequency of 30 Hz eliminates frequencies higher than 30 Hz, which seem to be of no relevance in our simulations. By applying this filtering process also the behavior of the signal acquisition by a defibrillator is simulated in a reasonable way.

(2) Ventricular fibrillation algorithms

(i) Reliability of Old and New Ventricular Fibrillation Detection Algorithms for Automated External Defibrillators

BioMedical Engineering OnLine 2005, 4:60 by A. Amann, R. Tratnig, and K. Unterkofler.

(ii) A New Ventricular Fibrillation Detection Algorithm for Automated External Defibrillators

Computers in Cardiology 32 (2005), 559-562 by A. Amann, R. Tratnig, and K. Unterkofler.

(iii) Detecting Ventricular Fibrillation by Time-Delay Methods

Transactions on Biomedical Engineering 54 (2007), 174 - 177, by A. Amann, R. Tratnig, and K. Unterkofler.

(3) CPR-filter algorithms

(i) Removal of Resuscitation Artefacts from Ventricular Fibrillation ECG Signals Using Kalman Methods

Computers in Cardiology 32 (2005), 555-558 by K. Rheinberger, M. Baubin, K. Unterkofler, and A. Amann.

(ii) Removing CPR Artifacts from the Ventricular Fibrillation ECG by Enhanced Adaptive Regression on Lagged Reference Signals

Computers in Cardiology (2006), by K. Rheinberger, K. Unterkofler, M. Baubin, and A. Amann.

(iii) Removal of CPR Artifacts from the Ventricular Fibrillation ECG by Adaptive Regression on Lagged Reference Signals

Transactions on Biomedical Engineering 55 (2008), 130 - 137, by K. Rheinberger, T. Steinberger, K. Unterkofler, M. Baubin, A. Klotz, and A. Amann.

(4) Diploma theses and PhD theses

(i) Creation of a Simulation Environment in Simulink/Matlab for the Analysis and Optimization of the Spectral Algorithm for the Detection of Ventricular Fibrillation diploma thesis 2004 by M. Fetz.

(ii) Automatic System to Test Semiautomatic External Debrillators for Sensitivity and Specificity diploma thesis 2004 by H. Säly.

(iii) Reliability of New Fibrillation Detection Algorithms for Automated External Defibrillators thesis 2005 by R. Tratnig.

(iv) The Ventricular Fibrillation Electrocardiogram: Datamanagement, Artefact Removal, Rating, and Defibrillation thesis 2006 by K. Rheinberger.