Ventricular fibrillation exhibits dynamical properties and self-similarity

The effect of ischemia on ventricular fibrillation as measured by fractal dimension and frequency measures

“…In prior studies the frequency based measures have shown a clear tendency to decrease with the duration of VF [4,5,7,8,16]. This implies that decreasing frequency is an indicator of prolonged VF.…”

“…The scaling exponent (ScE), LAC, and Hurst exponent have been well characterized in a large group of swine in earlier experimental work [7,9,14]. They show an increase in the fractal dimension over time.…”

“…Earlier laboratory studies have demonstrated that VF waveform analysis methods can provide an estimate of the duration of VF from the recorded electrocardiogram for use in treatment algorithms [4][5][6][7][8][9][10]. These methods exploit the two main features of the VF waveform, namely, frequency and roughness.…”

“…Early VF which has large smooth contours has a dimension near 1.1 and this gradually increases with VF duration to a dimension of 1.5 or greater as the waveform becomes more irregular. [7,9] The three frequency based measures have been studied extensively and include median frequency, angular velocity, and frequency ratio [4][5][6][7][8]12,16]. Measures of the fractal dimension have also been developed to analyze VF and include the scaling exponent (ScE) [9,[13][14][15] and the logarithm of the absolute correlations (LAC) [17].…”

“…Measures of the fractal dimension have also been developed to analyze VF and include the scaling exponent (ScE) [9,[13][14][15] and the logarithm of the absolute correlations (LAC) [17]. Another measure of fractal dimension is the Hurst exponent [7,[18][19][20]. The Hurst exponent indicates the degree to which the values in a waveform deviate from being random.…”