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Correntropy-based Analysis of Respiratory Patterns with Chronic Heart Failure
Garde Martínez, Ainara; Sörnmo, Leif; Jané Campos, Raimon; Giraldo Giraldo, Beatriz
Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial; Universitat Politècnica de Catalunya. SISBIO - Senyals i Sistemes Biomèdics
A correntropy-based technique is proposed for the analysis and characterization of respiratory flow signals in chronic heart failure (CHF) patients with both periodic and nonperiodic breathing (PB and nPB), and healthy subjects. Correntropy is a novel similarity measure which provides information on temporal structure and statistical distribution simultaneously. Its properties lend itself to the definition of the correntropy spectral density (CSD). An interesting result from CSD-based spectral analysis is that both the respiratory frequency and modulation frequency can be detected at their original positions in the spectrum without prior demodulation of the flow signal. The respiratory pattern is characterized by a number of spectral parameters extracted from the respiratory and modulation frequency bands. The results show that the power of the modulation frequency band offers excellent performance when classifying CHF patients versus healthy subjects, with an accuracy of 95.3%, and nPB patients versus healthy subjects with 90.7%. The ratio between the power in the modulation and respiration frequency bands provides the best results classifying CHF patients into PB and nPB, with an accuracy of 88.9%.
Peer Reviewed
Àrees temàtiques de la UPC::Enginyeria biomèdica::Electrònica biomèdica
Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica
Medical signal processing
Chronic heart failure
Processament digital -- Biomedicina
Cardiologia -- Informàtica
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/conferenceObject
         

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