M.S. Dahwah – Post-graduate Student, 
Mari State University
E-mail: eng_dahwah@yahoo.com

Cardiovascular disease has been identified as one of the biggest causes of death even in developed countries. One of the causes of death due to cardiovascular disease is associated with the fact that the risks are either not identified, or they are identified only at a later stage. However, the creation and development of software for ECG research and analysis has been the most important scientific task for over 30 years. Of particular interest for ECG analysis is due to its role as an effective non-invasive research method that provides useful information for the detection, diagnosis and treatment of heart disease. In addition, correctly identifying the ECG shape can help achieve more accurate results in applications such as pattern recognition or classification.
Various digital signal processing techniques are used to detect the various components of the ECG. Creation and development of software for QRS research and analysis has been the most important scientific task for over 30 years. The purpose of this paper is to develop a low computational algorithm for detecting the QRS complex and its features of an ECG signal, this can be achieved by solving the following tasks: analysis of existing algorithms in ECG processing that based on the wavelet transform;  improvements QRS complex detection algorithm with its evaluation.
This article proposes a simple and effective adaptive algorithm for QRS detection in ECG. Initially, the data is preprocessed in two stages: wavelet decomposition and reconstruction, after which an adaptive threshold detection algorithm was used. The adaptive threshold is applied to detect the peaks in the QRS region, which are Q and R and S. This algorithm is quite simple to calculate, efficient and detects QRS with high reliability. The proposed algorithm is evaluated using ECG signals from the PhysioNet database Challenge 2017. Based on the results of the work carried out, the following conclusions were made: 1) developed application software for ECG processing; proposed and implemented an algorithm for detecting QRS complexes; 3) proposed and implemented an algorithm for the adaptive threshold of R-peak detection. The algorithm has a high performance: TPR = 99.98%, PPV = 100%.

Dahwah M.S. Adaptive algorithm of qrs-complex features detection, based on wavelet transform. Electromagnetic waves and electronic systems. 2020. V. 25. № 4. P. 37−45. DOI: 10.18127/j15604128-202004-05. (in Russian)

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