| Abstract: |  This diploma thesis deals with assessment of different heart rate analysis methods for distinguishing between atrial fibrilation and normal sinus rhythm. Many
linear and nonlinear methods, such as NN50, pNN50, RMSSD, SDNN, SDSD, short
term variability, long term irregularity, SDANN, SDNNind, delta, interval index,
coeficient of variation, mean of RR intervals, mean of heart rate, Poincaré plot,
detrended fluctuation analysis, approximate entropy, sample entropy, Shannon entropy, box counting dimension and Sevcik estimate for fractal dimension were tested and the reached results are presented. As the most promising features the following
were found: slow detrended
fluctuation analysis and ratio of axes in the Poincaré
plot PcPSD12. Both features had high level of significance according to Mann-Whitney test. In this work not only theoretical analysis of the methods is provided, also practical implementation of the methods was done in form of program with
user-friendly graphical interface.
Finally, the simple classification of data was undertaken for evaluation of the practical usability of the features. As a result classification using arbitrary decision
tree in WEKA brought us results of 92,1 % specificity and 92 % sensitivity in distinguishing between atrial fibrillation and normal sinus rhythm - results comparable to those in recent articles.
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