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Most methods of morphological analysis of the electrocardiogram (ECG) are based on the search for R-wave. Knowing the position of the R-wave, it is rather simple to determine the remaining components of the QRS complex. The main problems of machine detection of the R-wave are ECG trace artifacts and high variability of cardiac complexes. The algorithm for detecting the QRS-complex consisting of two stages is proposed and implemented. At the preliminary stage, time-frequency transformations as in the Pan-Tompkins detector are used to remove noise and non-informative ECG components. The algorithm has adaptive parameters to account for the variability of R-wave. The arithmetic mean and the standard deviation of the height of the preceding R-wave and the lengths of the RR intervals are used as these parameters. At the main stage of the algorithm, adaptive parameters are used to predict the characteristics of the next R-wave. A function evaluating the difference between the current metrics of the conditional R-wave with a vertex at the given point and the expected ones is proposed. The minimum of the given function on a given interval is a criterion for the detection of the R-wave. The software implementation of the algorithm showed high sensitivity and specificity on MIT-BIH test databases. The algorithm can be used in cardiomonitors, automatic defibrillators, artificial pacemakers with feedback and other devices with real-time ECG processing

Algorithm for detecting QRS-complex on the electrocardiogram in real-time mode