Document Detail

Multi-channel classification of respiratory sounds.
MedLine Citation:
PMID:  17946985     Owner:  NLM     Status:  MEDLINE    
In this study, respiratory sounds of pathological and healthy subjects were analyzed via frequency spectrum and AR model parameters with a view to construct a diagnostic aid based on auscultation. Each subject is represented by 14 channels of respiratory sound data of a single respiration cycle. Two reference libraries, pathological and healthy, were built based on multi-channel respiratory sound data for each channel and for each respiration phase, inspiration and expiration, separately. A multi-channel classification algorithm using K nearest neighbor (k-NN) classification method was designed. Performances of the two classifiers using spectral feature set corresponding to quantile frequencies and 6th order AR model coefficients on inspiration and expiration phases are compared.
C Asli Yilmaz; Yasemin P Kahya
Related Documents :
12656355 - Impedance measurements around grazing incidence for nonlocally reacting thin porous lay...
18247735 - Accelerometer measurements of acoustic-to-seismic coupling above buried objects.
19045565 - Mid-frequency sound propagation through internal waves at short range with synoptic oce...
22087905 - Acoustical properties of double porosity granular materials.
25083945 - Picosecond-to-nanosecond dynamics of plasmonic nanobubbles from pump-probe spectral mea...
20039715 - Stereodynamics at the gas-liquid interface: orientation and alignment of co2 scattered ...
Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference     Volume:  1     ISSN:  1557-170X     ISO Abbreviation:  Conf Proc IEEE Eng Med Biol Soc     Publication Date:  2006  
Date Detail:
Created Date:  2007-10-23     Completed Date:  2008-03-13     Revised Date:  2014-08-21    
Medline Journal Info:
Nlm Unique ID:  101243413     Medline TA:  Conf Proc IEEE Eng Med Biol Soc     Country:  United States    
Other Details:
Languages:  eng     Pagination:  2864-7     Citation Subset:  IM    
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Auscultation / methods*
Diagnosis, Computer-Assisted / methods*
Neural Networks (Computer)
Pattern Recognition, Automated / methods*
Reproducibility of Results
Respiration Disorders / diagnosis*,  physiopathology*
Respiratory Sounds / classification*
Sensitivity and Specificity
Sound Spectrography / methods*

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

Previous Document:  Detection and adaptive cancellation of heart sound interference in tracheal sounds.
Next Document:  Bayesian tracking of a nonlinear model of the capnogram.