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Multidatabase ECG signal processing

机译:多数据库心电图信号处理

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An Electrocardiogram (ECG) records the electrical activity of the heart to locate the abnormalities. ECG signal processing is an emerging tool for the cardiologists in medical diagnosis for effective treatments. Many researches focus on how to improve preprocessing and processing algorithms in order to classify ECG signals with low cost and high accuracy. These algorithms consist of removing all types of noise that contaminate the ECG recording as well as extracting the most important features. In this paper, we present a useful Matlab GUI to analyze and classify ECG signal using efficient preprocessing and processing techniques. These techniques allow acquiring ECG recorders from various universal cardiac databases, filtering them using Butterworth low pass filter and IIR notch filter and extracting the most important cardiac features based on discrete wavelet transform db6.
机译:心电图(ECG)记录心脏的电活动以定位异常。心电图信号处理是心脏病专家进行医学诊断以进行有效治疗的新兴工具。许多研究集中于如何改进预处理和处理算法,以便以低成本和高精度对ECG信号进行分类。这些算法包括消除污染ECG记录的所有类型的噪声以及提取最重要的功能。在本文中,我们提出了一个有用的Matlab GUI,可以使用高效的预处理和处理技术对ECG信号进行分析和分类。这些技术允许从各种通用心脏数据库中获取ECG记录器,使用Butterworth低通滤波器和IIR陷波滤波器对其进行过滤,并基于离散小波变换db6提取最重要的心脏特征。

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