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
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
Recommended Citation
Alzona, W. M., Co, C. T., David, L. B., & Villaseran, P. O. (2008). DSP board-based pulmonary symptoms detection using sound processing through acoustical stethoscope. Retrieved from https://animorepository.dlsu.edu.ph/etd_bachelors/14376