Reference for citation: Akopyan B. K. Classification of heart rhythm disorder episodes by informative features in the electrocardiogram time domain. Journal of Instrument Engineering. 2024. Vol. 67, N 4. P. 305—314 (in Russian). DOI: 10.17586/0021-3454-2024-67-4-305-314.

Abstract. The features of heart rhythm disturbances classification based on the electrocardiogram obtained from one lead are studied. A primary set of eight informative features is proposed: three for the RR-interval duration and five for the R-waveshape. An effective combination of the proposed features for classification of three states of heart rhythm (normal cardio cycle, ventricular extrasystole, atrial extrasystole) using algorithms of logistic regression and random forest is proposed. The records of II lead from multi-channel electrocardiograms databases of MIT-BIH Arrhythmia DB and St.-Petersburg Institute of Cardiological Engineering „INCART“ are applied. It is found that the most informative features for the considered classes of cardiac rhythm disorders are the clutch coefficient and the i-th R-wave kurtosis coefficient γi. The best accuracy of classification according to the average balanced F-measure for dataset without class balancing is 92.58 % for logistic regression and 92.11 % for random forest; with class balancing the result is 86.17 % for logistic regression and 84.55 % for random forest. The experimental results show that to classify the heart rhythm disturbances under consideration, it is advisable to use one criterion of duration and form. The obtained results can be used in the synthesis and analysis of classification systems for heart rhythm disorders.

Keywords: space of informative features, multiclass classification, electrocardiogram, cardiac arrhythmia, data analysis

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