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Please use this identifier to cite or link to this item: http://hdl.handle.net/10506/682

Title: Clustering and visualization of ECG signals
Authors: Vágner, Anikó
Farkas, László
Juhász, István
Keywords: clustering
ECG signals
Issue Date: 2011
Publisher: Springer-Verlag Berlin Heidelberg 2011
Citation: Vágner, Anikó, Farkas, László, Juhász, István (2011), Clustering and visualization of ECG signals, Advances in Intelligent and Soft Computing, 2011, Volume 101, Third International Conference on Software, Services and Semantic Technologies S3T 2011, September 1-3, 2011, Bourgas, Bulgaria, ISBN 978-3-642-23162-9, pp. 47-51
Abstract: Holter electrocardiographic (ECG) signals are ambulatory long-term registers used to detect heart diseases. These signals normally include more, than one channels and its duration is up to 24 hours. The principal problem of the cardiologists is the manual inspection of the whole Holter ECG to find all those beats which morphology differs from the normal beats. In this paper we present our method. We apply firstly a grid clustering technique. Secondly we use a special density-based clustering algorithm, named Optics. Then we visualize every heart beat in the record, heartbeats in a cluster, furthermore we represent every cluster with median of heartbeats. We can perform manual and further automatic clustering. With this method, the result is easy ECG analysis and optimization of time of processing.
URI: http://hdl.handle.net/10506/682
ISBN: 978-3-642-23162-9
ISSN: 1867-5662
Appears in Collections:S3T 2011

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