Detection of compressed tracheal sound patterns with large amplitude variation during sleep.

Abstract:

:The objective of the present work was to develop automated methods for the compressed tracheal breathing sound analysis. Overnight tracheal breathing sound was recorded from ten apnoea patients. From each patient, three different types of tracheal sound deflection pattern, each of 10 min duration, were visually scored, viewing the compressed tracheal sound curve. Among them, high deflection patterns are of special interest due to the possible correlation with apnoea-hypopnoea sequences. Three methods were developed to detect patterns with high deflection, utilizing nonlinear filtering in local characterization of tracheal sounds. Method one comprises of local signal maximum, the second method of its local range, and the third of its relative range. The three methods provided 80% sensitivity with 57, 91 and 93% specificity, respectively. Method three provided an amplitude-independent approach. The nonlinear filtering based methods developed here offer effective means for analysing tracheal sounds of sleep-disordered breathing.

journal_name

Med Biol Eng Comput

authors

Kulkas A,Rauhala E,Huupponen E,Virkkala J,Tenhunen M,Saastamoinen A,Himanen SL

doi

10.1007/s11517-008-0317-z

subject

Has Abstract

pub_date

2008-04-01 00:00:00

pages

315-21

issue

4

eissn

0140-0118

issn

1741-0444

journal_volume

46

pub_type

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