Breathing pattern characterization in chronic heart failure patients using the respiratory flow signal.
Ann Biomed Eng
; 38(12): 3572-80, 2010 Dec.
Article
em En
| MEDLINE
| ID: mdl-20614249
ABSTRACT
This study proposes a method for the characterization of respiratory patterns in chronic heart failure (CHF) patients with periodic breathing (PB) and nonperiodic breathing (nPB), using the flow signal. Autoregressive modeling of the envelope of the respiratory flow signal is the starting point for the pattern characterization. Spectral parameters extracted from the discriminant frequency band (DB) are used to characterize the respiratory patterns. For each classification problem, the most discriminant parameter subset is selected using the leave-one-out cross-validation technique. The power in the right DB provides an accuracy of 84.6% when classifying PB vs. nPB patterns in CHF patients, whereas the power of the DB provides an accuracy of 85.5% when classifying the whole group of CHF patients vs. healthy subjects, and 85.2% when classifying nPB patients vs. healthy subjects.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Respiração
/
Insuficiência Cardíaca
Tipo de estudo:
Etiology_studies
/
Observational_studies
/
Prognostic_studies
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Risk_factors_studies
Limite:
Adult
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Aged
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Revista:
Ann Biomed Eng
Ano de publicação:
2010
Tipo de documento:
Article
País de afiliação:
Espanha