ECG Data Mining Using SAS

G.K. Kuatbayeva, Ryskhan Satybaldiyeva, Zarina Syrymbet, A. A. Kuatbayeva, Meruert Mankibayeva

2020

Closed access Metadata (CSL-JSON)
DOI 10.1109/cbi49978.2020.10061
Data confidence 70 medium
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Abstract

ECG analysis is an important part of finding devices, especially in the cardiovascular system. Various parameters obtained with the ECG curve, such as P-R, QT, R-R, Q-R-S, and S-T intervals, as well as heart rate variability, serve as safety and efficacy endpoints for many clinical trials. There are different algorithms based on graphs and frequency domains to detect different waveforms and ECG cells [4]. This article discusses the study and determination of ECG using SAS. ECG data, which are used for analysis and articles in clinical, are usually processed. The study of the algorithm of ECG signs using SAS allows you to flexibly and clearly perform a preliminary analysis of the parameters obtained from the ECG. In addition, it allows the programmer or researcher to analyze the same data from a research point of view.