Digital Analysis of Asthmatic Cough Sounds.
- Author:
Man Yong HAN
1
;
Cheol Woo JO
Author Information
1. Department of Pediatrics, Pundang CHA General Hospital, College of Medicine, Pochon CHA University, Sungnam, Korea.
- Publication Type:Original Article
- Keywords:
Asthma;
Computer-assisted, Cough;
Signal processing, Sound
- MeSH:
Acoustics;
Asthma;
Classification;
Cough*;
Diagnosis;
Humans;
Logistic Models;
Sensitivity and Specificity;
Signal Processing, Computer-Assisted
- From:Pediatric Allergy and Respiratory Disease
1999;9(4):360-368
- CountryRepublic of Korea
- Language:Korean
-
Abstract:
PURPOSE: Cough is a frequent symptom in bronchial asthma. Acoustic digital analysis of cough has been reported using digital signal processing techniques. Differences between asthmatic and control cough sounds are presented. The main purpose of this study was to examine whether overall spectral energy and the visual observation of the fine details of the cough spectrographs, explain the differences in cough between normal subjects and asthmatic patients. METHODS: We presented data from 7 asthmatic patients and 8 non-asthmatic subjects using a new method of acoustic analysis. Cough sound was digitalized at a sampling rate of 5 kHz. Individual coughs were divided into two or three phases, presents the data of RMS (Root Mean Square), duration, RMS in the frequency band. Factor analysis and iogistic regression analysis were performed to identify groups of variables. RESULTS: Duration of cough was longer in asthmatics cough. The number of additional cough sounds showed no difference. RMS of cough in total cough and 2nd phase cough was stronger for asthmatics cough. Energy of frequency band is significantly different in 1,000-1,500 Hz, 1,500-2,000 Hz, 5,000-5,500 Hz, 5,500-6,000 Hz, 6,000-6,500 Hz, 9,000-9,500 Hz at total phase, 0-500 Hz, 1,000-1,500 Hz, 2,000-2,500 Hz, 5,000-5,500 Hz, 6,000-6,500 Hz, 9,000-9,500 Hz at 1st phase. Factor analysis and logistic regression analysis for the two groups provoded a classification table of 96.3% of sensitivity and 86.0% of specificity. CONCLUSION: We provided a new approach to the analysis of cough sounds. Significant differences were found between asthmatic and non-asthmatic cough sounds. It has potential as a tool with which to study the pathophysiology of cough and diagnosis the respiratory disease.
