Document Detail

Correntropy-based spectral characterization of respiratory patterns in patients with chronic heart failure.
MedLine Citation:
PMID:  20211799     Owner:  NLM     Status:  MEDLINE    
A correntropy-based technique is proposed for the characterization and classification of respiratory flow signals in chronic heart failure (CHF) patients with periodic or nonperiodic breathing (PB or nPB, respectively) and healthy subjects. The correntropy is a recently introduced, generalized correlation measure whose properties lend themselves to the definition of a correntropy-based spectral density (CSD). Using this technique, both respiratory and modulation frequencies can be reliably detected at their original positions in the spectrum without prior demodulation of the flow signal. Single-parameter classification of respiratory patterns is investigated for three different parameters extracted from the respiratory and modulation frequency bands of the CSD, and one parameter defined by the correntropy mean. The results show that the ratio between the powers in the modulation and respiratory frequency bands provides the best result when classifying CHF patients with either PB or nPB, yielding an accuracy of 88.9%. The correntropy mean offers excellent performance when classifying CHF patients versus healthy subjects, yielding an accuracy of 95.2% and discriminating nPB patients from healthy subjects with an accuracy of 94.4%.
Ainara Garde; Leif Sörnmo; Raimon Jané; Beatriz F Giraldo
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2010-03-04
Journal Detail:
Title:  IEEE transactions on bio-medical engineering     Volume:  57     ISSN:  1558-2531     ISO Abbreviation:  IEEE Trans Biomed Eng     Publication Date:  2010 Aug 
Date Detail:
Created Date:  2010-07-27     Completed Date:  2010-11-05     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0012737     Medline TA:  IEEE Trans Biomed Eng     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1964-72     Citation Subset:  IM    
Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya, Barcelona 08028, Spain.
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MeSH Terms
Chronic Disease
Computer Simulation
Heart Failure / physiopathology*
Nonlinear Dynamics
Pattern Recognition, Automated / methods*
Reproducibility of Results
Respiratory Function Tests / methods*
Respiratory Mechanics / physiology*
Signal Processing, Computer-Assisted*

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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