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http://dx.doi.org/10.5391/IJFIS.2013.13.1.31

Electrocardiogram Signal Compression with Reconstruction via Radial Basis Function Interpolation Based on the Vertex  

Ryu, Chunha (School of Engineering and Computer Science, Kyungpook National University)
Kim, Tae-Hun (School of Engineering and Computer Science, Kyungpook National University)
Kim, Jungjoon (School of Engineering and Computer Science, Kyungpook National University)
Choi, Byung-Jae (School of Electronic and Electrical Engineering, Daegu University)
Park, Kil-Houm (School of Engineering and Computer Science, Kyungpook National University)
Publication Information
International Journal of Fuzzy Logic and Intelligent Systems / v.13, no.1, 2013 , pp. 31-38 More about this Journal
Abstract
Patients with heart disease need long-term monitoring of the electrocardiogram (ECG) signal using a portable electrocardiograph. This trend requires the miniaturization of data storage and faster transmission to medical doctors for diagnosis. The ECG signal needs to be utilized for efficient storage, processing and transmission, and its data must contain the important components for diagnosis, such as the P wave, QRS-complex, and T wave. In this study, we select the vertex which has a larger curvature value than the threshold value for compression. Then, we reconstruct the compressed signal using by radial basis function interpolation. This technique guarantees a lower percentage of root mean square difference with respect to the extracted sample points and preserves all the important features of the ECG signal. Its effectiveness has been demonstrated in the experiment using the Massachusetts Institute of Technology and Boston's Beth Israel Hospital arrhythmia database.
Keywords
Electrocardiogram; Data compression; Radial basis function; Interpolation; Vertex; Signal reconstruction;
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Times Cited By KSCI : 3  (Citation Analysis)
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