DSP board-based pulmonary symptoms detection using sound processing through acoustical stethoscope

Date of Publication

2008

Document Type

Bachelor's Thesis

Degree Name

Bachelor of Science in Electronics and Communications Engineering

Subject Categories

Engineering

College

Gokongwei College of Engineering

Department/Unit

Electronics and Communications Engineering

Thesis Adviser

Edwin Sybingco

Defense Panel Chair

Enrique M. Manzano

Defense Panel Member

Antonio S. Gonzales, Jr.

Miguel O. Gutierrez

Abstract/Summary

In this paper, an automatic wheeze and crackle detection system is developed. Lung sounds are recorded in a wave file using an acoustical stethoscope amplifier circuit connected to the Blackfin 537 DSP board. The spectrogram is generated from the recorded wave file using Fast Fourier Transfor (FFT). The spectrogram image is passed through a bilateral filter and a limiter to increase the contrast and isolate the higher components. Image processing is used to detect wheezes in the image. Katz-Sevcik fractal dimension (KSFD) is then used to detect crackles. KSFD measures the complexity of a signal. Applying the concepts and techniques used in this study, the system was able to correctly detect normal sounds with an accuracy of 75%, wheezes with an accuracy of 62.5% and crackles with an accuracy of 91.67%.

Abstract Format

html

Language

English

Format

Print

Accession Number

TU14382

Shelf Location

Archives, The Learning Commons, 12F, Henry Sy Sr. Hall

Physical Description

262 leaves : ill. (some col.) ; 28 cm.

Keywords

Acoustical engineering; Stethoscopes; Auscultation; Respiratory organs--Sounds; Pulmonary manifestations of general diseases; Sound waves

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