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Proceedings Paper

Effectiveness of morphological and spectral heartbeat characterization on arrhythmia clustering for Holter recordings
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Paper Abstract

Heartbeat characterization is an important issue in cardiac assistance diagnosis systems. In particular, wide sets of features are commonly used in long term electrocardiographic signals. Then, if such a feature space does not represent properly the arrhythmias to be grouped, classification or clustering process may fail. In this work a suitable feature set for different heartbeat types is studied, involving morphology, representation and time-frequency features. To determine what kind of features generate better clusters, feature selection procedure is used and assessed by means clustering validity measures. Then the feature subset is shown to produce fine clustering that yields into high sensitivity and specificity values for a broad range of heartbeat types.

Paper Details

Date Published: 28 January 2015
PDF: 7 pages
Proc. SPIE 9287, 10th International Symposium on Medical Information Processing and Analysis, 92870A (28 January 2015); doi: 10.1117/12.2070686
Show Author Affiliations
Cristian Castro-Hoyos, Univ. Nacional de Colombia (Colombia)
Diego Hernán Peluffo-Ordóñez, Univ. Cooperativa de Colombia (Colombia)
Jose Luis Rodríguez-Sotelo, Univ. Autónoma de Manizales (Colombia)
Germán Castellanos-Domínguez, Univ. Nacional de Colombia (Colombia)


Published in SPIE Proceedings Vol. 9287:
10th International Symposium on Medical Information Processing and Analysis
Eduardo Romero; Natasha Lepore, Editor(s)

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