The aim of this paper is to describe an automatic classifier to assess the severity of congestive heart failure (CHF) patients. Disease severity is defined according to the New York Heart Association classification (NYHA). The proposed classified aims to distinguish very mild CHF (NYHA I) from mild (NYHA II) and severe CHF patients (NYHA III), using long-term nonlinear Heart Rate Variability (HRV) measures. 24h Holter ECG recording from 2 public databases was performed, including 44 patients suffering from CHF. One non-linear HRV feature was effective in distinguishing very-mild CHF from mild CHF, by achieving a sensibility and specificity rate of 75% and 100% respectively. Moreover, we combine the results obtained by LDA in a classification tree (previously described) in order to obtain an automatic classifier for CHF severity assessment. © Springer International Publishing Switzerland 2014.

Heart rate variability for automatic assessment of congestive heart failure severity

MELILLO, Paolo;
2014

Abstract

The aim of this paper is to describe an automatic classifier to assess the severity of congestive heart failure (CHF) patients. Disease severity is defined according to the New York Heart Association classification (NYHA). The proposed classified aims to distinguish very mild CHF (NYHA I) from mild (NYHA II) and severe CHF patients (NYHA III), using long-term nonlinear Heart Rate Variability (HRV) measures. 24h Holter ECG recording from 2 public databases was performed, including 44 patients suffering from CHF. One non-linear HRV feature was effective in distinguishing very-mild CHF from mild CHF, by achieving a sensibility and specificity rate of 75% and 100% respectively. Moreover, we combine the results obtained by LDA in a classification tree (previously described) in order to obtain an automatic classifier for CHF severity assessment. © Springer International Publishing Switzerland 2014.
9783319008455
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11591/374822
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