Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/77780
Title: Noise cancellation algorithm for respiratory sound analysis
Authors: Low, Yee Jin
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2019
Abstract: Respiratory diseases such as pneumonia have been one of the top principal causes of death in Singapore from 2015 to 2017. With more people visiting the doctors in hospitals for health check-ups, it has become important for the doctor examining the patient to be able to distinguish between the background noise and the lung sound. Lung breathing sounds are an important part of the respiratory examination and is helpful in diagnosing various respiratory disorders. Lung respiratory sounds assess airflow through the trachea-bronchial tree. It is important to distinguish such sounds from abnormal ones like crackles and wheezes in order to make an accurate diagnosis; especially when there is background noise, it will make this task of doing so much tougher. In this project, the student will be focusing on the developing of a MATLAB algorithm to be able to help doctors distinguish between lung respiratory sounds and abnormal sounds by removing as much background noise as possible through the algorithm.
URI: http://hdl.handle.net/10356/77780
Schools: School of Electrical and Electronic Engineering 
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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