Statistical Fractal Analysis of Cardiac Dynamic Behavior

Abstract

The complexity of those systems that can be studied from frequency distributions can be characterized with the statistical fractal dimension. A methodology of diagnostic evaluation of the cardiac dynamics was developed from this dimension, allowing differentiating normal dynamics from those with acute dynamics. For this study, 30 holter and continuous electrocardiographic records clinically diagnosed with acute dynamic were analyzed, also 20 dynamics clinically diagnosed as normal were taken. For each dynamic the values of maximal and minimal values by hour of cardiac frequencies were taken; with these values, the statistical fractal dimension were calculated, for this, the values were organized in ranges of 15 beat/min, and the number of times each range was presented was founded. To this distribution of numbers, the Zipf-Mandelbrot law was applied for find the fractal dimension of each dynamic. Subsequently, the diagnosis evaluation methodology was applied, and the sensitivity, specificity and Kappa coefficient values were measured, finding values for the sensitivity and specificity of 100%, and a Kappa coefficient. Through of application of diagnosis evaluation methodology was possible differentiate normality of acute disease in the cardiac dynamic.