DocumentCode :
718475
Title :
Detection of COPD´s diagnostic signs based on polyspectral lung sounds analysis of respiratory phases
Author :
Poreva, Anna ; Karplyuk, Yevgeniy ; Makarenkova, Anastasiia ; Makarenkov, Anatoliy
Author_Institution :
Phys. & Biomed. Electron. Dept., Nat. Tech. Univ. of Ukraine, Kiev, Ukraine
fYear :
2015
fDate :
21-24 April 2015
Firstpage :
351
Lastpage :
355
Abstract :
This study examines the method for determining the specific auscultatory diagnostic signs in patients with chronic obstructive pulmonary disease (COPD). The main idea of the method is based on the finding of these features in separate respiratory phases of lung sound. For this purpose the original algorithm which divides the sound signal to inspiration and expiration phases was developed. Each phase was analyzed separately using polyspectral analysis methods. Diagnostic features were determined on the basis of the construction of three-dimensional bicoherence function and calculating the bicoherence and skewness coefficients. The set of all calculated characteristics made it possible to evaluate each respiratory phase. This allows to conclude about the presence or absence of auscultatory artifacts as pathology indicators.
Keywords :
bioacoustics; diseases; lung; medical signal detection; medical signal processing; patient diagnosis; pneumodynamics; spectral analysis; COPD diagnostic sign detection; auscultatory artifacts; auscultatory diagnostic signs; bicoherence coefficient; chronic obstructive pulmonary disease; diagnostic features; expiration; inspiration; pathology indicators; polyspectral analysis methods; polyspectral lung sounds analysis; respiratory phases; skewness coefficient; three-dimensional bicoherence function; Algorithm design and analysis; Conferences; Diseases; Lungs; Nanotechnology; Noise; Pathology; COPD; bicoherence coefficient; bifrequency; lung sound; respiratory phases; skewness coefficient;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronics and Nanotechnology (ELNANO), 2015 IEEE 35th International Conference on
Conference_Location :
Kiev
Type :
conf
DOI :
10.1109/ELNANO.2015.7146908
Filename :
7146908
Link To Document :
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