Common dynamic properties of biosignals during cognition: self-similarity and chaotic dynamics of both response times and EEG during movement imagery.

This study was undertaken to verify whether different output variables or biosignals, measured during performance of a cognitive task, manifest common dynamical properties. Nonlinear properties of both response times (RTs) and electroercephalograms (EEG) were tested. We asked subjects to generate mental images of actions following of auditorily presentation simple phrases suggesting the action. Analysis of RT series combined from many subjects and of EEG records from single subjects clearly manifested self-similarity and chaotic dynamics that provide insights into the self-organization of the brain/behavioral system.

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).