Time-Frequency Analysis of Electric Cardiograms
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-Frequency Analysis of Electric Cardiograms B. A. Oganisyana, T. N. Oganesyana, and A. O. Makaryana, * a
Yerevan State University, Yerevan, Armenia *e-mail: [email protected]
Received March 27, 2020; revised April 30, 2020; accepted May 12, 2020
Abstract—In the present work, statistical processing of the electric cardiogram (spectral and bispectral analysis) using the ‘sliding window’ method is proposed and performed. A system for recording and digitizing an electric cardiograms was developed, the output signal of which is fed to a computer. Signal processing is carried out using a system implemented in the LabVIEW environment. It is shown that the time-frequency analysis using the ‘sliding window’ method allows detecting dynamic processes in the work of the human heart, which can go unnoticed in standard analyzes. Research results can be useful for the diagnosis of heart disease. Keywords: ECG, statistical signal processing, spectrum, bispectral analysis DOI: 10.3103/S1068337220040155
1. INTRODUCTION Modern functional diagnostics of human health has a variety of instrumental research methods, some of which are available only to a narrow circle of specialists. One of the most widespread and accessible research methods is electrography—registration of biopotentials of tissues and organs. However, the specific names of the corresponding diagnostic methods are more common: electrocardiography (ECG)— registration of biopotentials arising in the heart muscle when it is excited, electromyography (EMG)— registration of bioelectrical activity of muscles, electroencephalography (EEG)—registration bioelectrical activity of the brain, etc. Obtaining of biopotentials directly from the organ—heart, brain, etc. (invasive method) in most cases is associated with great difficulties. Therefore, often biopotentials are obtained by electrodes from other neighboring external tissues, on which electrical potentials are induced by the examined organ (non-invasive method). The main method for studying the dynamics of the development of cardiovascular diseases is electrocardiography [1, 2], since it is a non-invasive method and does not cause particular concern to the patient. The direct result of electrocardiography is to obtain an electrocardiogram signal (ECG signal)—a graphical representation of the potential difference arising from the work of the heart. The ECG signal reflects all the acting potentials that arise during the work of the heart. After the first works of O. Waller [3, 4] and V. Einthoven [4], at the end of the 19th century, the method of recording an ECG signal was intensively improved for the registration of the EGG. Despite more than 100 years of history of the use in clinical practice, electric cardiography still remains a popular method for diagnosing cardiovascular diseases. One of the important points of collecting data on the state of heart health is the obtaining and analysis of the electrocardiogram [1, 2, 4]. There is a wide range of devices for recording ECG signals. Some of them are also capable of analyzing t
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