Open AccessPreliminary Detection of Lung Diseases in Pediatric Population using Soft Computing
Author(s) -
Sibghatullah I. Khan,
Syed Jahangir Badashah,
Mallikarjun Mudda
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.b2005.098319
Subject(s) - stethoscope , lung , computer science , population , artificial neural network , speech recognition , pattern recognition (psychology) , lung disease , artificial intelligence , medicine , radiology , environmental health
The investigations from recent studies clearly show the potential of lung sounds in detection of lung abnormalities in human subjects. This paper aims to analyze lung sounds acquired using special electronic stethoscope for detection adventitious sounds arising out of pathological lungs due to various disease like brochities especially in pediatric population. For acquisition and recording of lung sounds, 3M Littmann 3200 model is utilized. After verifying fidelity of electronic stethoscope, the analysis of lung sounds was carried out by various spectral and temporal features. The features extracted were fed to artificial neural network for classification. Various combinations of ANN with different topologies were experimented. The overall accuracy of obtained with one hidden layer GFF is 94.95%.