RT Journal Article
T1 A method for context-based adaptive QRS clustering in real-time
A1 Castro, Daniel
A1 Félix Lamas, Paulo
A1 Rodríguez Presedo, Jesús María
K1 QRS
K1 Clustering
K1 ECG
K1 Electrocardiogram
K1 Adaptive
K1 Realtime
K1 Context-based
K1 EKG
K1 Beat
K1 Heartbeat
AB Continuous follow-up of heart condition through long-term electrocardiogram monitoring is an invaluable tool for diagnosing some cardiac arrhythmias. In such context, providing tools for fast locating alterations of normal conduction patterns is mandatory and still remains an open issue. This work presents a real-time method for adaptive clustering QRS complexes from multilead ECG signals that provides the set of QRS morphologies that appear during an ECG recording. The method processes the QRS complexes sequentially, grouping them into a dynamic set of clusters based on the information content of the temporal context. The clusters are represented by templates which evolve over time and adapt to the QRS morphology changes. Rules to create, merge and remove clusters are defined along with techniques for noise detection in order to avoid their proliferation. To cope with beat misalignment, Derivative Dynamic Time Warping is used. The proposed method has been validated against the MIT-BIH Arrhythmia Database and the AHA ECG Database showing a global purity of 98.56% and 99.56%, respectively. Results show that our proposal not only provides better results than previous offline solutions but also fulfills real-time requirements.
PB IEEE
SN 2168-2194
YR 2014
FD 2014-10-08
LK http://hdl.handle.net/10347/11733
UL http://hdl.handle.net/10347/11733
LA eng
NO Castro, D., Félix, P., Presedo, J. (2014). A method for context-based adaptive QRS clustering in real-time. "IEEE Journal of Biomedical and Health Informatics" , [Documento en línea] doi: 10.1109/JBHI.2014.2361659
NO This work was supported by the Spanish Ministry of Science and Innovation (MICINN) under grant TIN2009-14372-C03-03.
DS Minerva
RD 4 may 2026