Javascript is not activated in your browser. This website needs javascript activated to work properly.
Du är här

Breathing pattern characterization in chronic heart failure patients using the respiratory flow signal

Publiceringsår: 2010
Språk: Engelska
Sidor: 3572-3580
Publikation/Tidskrift/Serie: Annals of Biomedical Engineering
Volym: 38
Nummer: 12
Dokumenttyp: Artikel
Förlag: Springer


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.



  • Medicine and Health Sciences
  • Respiratory pattern
  • Discriminant
  • Periodic and nonperiodic breathing
  • band
  • Chronic heart failure
  • AR modeling


  • Signal Processing
  • ISSN: 0090-6964

Box 117, 221 00 LUND
Telefon 046-222 00 00 (växel)
Telefax 046-222 47 20
lu [at] lu [dot] se

Fakturaadress: Box 188, 221 00 LUND
Organisationsnummer: 202100-3211
Om webbplatsen