Method for ventricular fibrillation detection in the external electrocardiogram using nonlinear prediction

The automatic external defibrillator is a lifesaving device which processes and analyses the electrocardiogram (ECG) and delivers defibrillation shock when necessary. The accuracy of the built-in algorithm for ECG analysis must be very high, with sensitivity and specificity aimed to approach the maximum values of 100%. An algorithm based on nonlinear prediction of the external ECG signal is proposed. It extracts seven parameters characterizing the prediction possibility of the assessed ECG signal. By means of the K-nearest neighbours rule the diagnostic accuracy of different combinations of these parameters was evaluated. Thus the accuracy obtained was higher than 95% with sensitivity and specificity values depending on the combination of parameters. The method was tested with ECG records from the widely recognized databases of the American Heart Association (AHA) and Massachusetts Institute of Technology (MIT).