Noise cancellation algorithm for respiratory sound classification

The lung is an important organ and an important health indicator of a human. Respiratory diseases are one of the top causes of death and disabilities in the world [1]. It has therefore become vital that the doctor is able to properly diagnose the lung health of a patient as more people go to the cli...

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Main Author: Soh, Marianne Hui Ying
Other Authors: Ser Wee
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2020
Subjects:
Online Access:https://hdl.handle.net/10356/139233
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1392332023-07-07T18:53:59Z Noise cancellation algorithm for respiratory sound classification Soh, Marianne Hui Ying Ser Wee School of Electrical and Electronic Engineering ewser@ntu.edu.sg Engineering::Bioengineering The lung is an important organ and an important health indicator of a human. Respiratory diseases are one of the top causes of death and disabilities in the world [1]. It has therefore become vital that the doctor is able to properly diagnose the lung health of a patient as more people go to the clinics and hospitals for their health check ups. Lung sounds such as wheezing and crackling indicates the presence of lung disease. With background noises and interferences, the doctor may not be able to give an accurate examination of the patient’s health. An adaptive filter has self-adjusting characteristics and adapts to changes in its input signals automatically. The objective of this project is to design an adaptive noise cancellation algorithm based on least mean square (LMS) filtering on MATLAB to improve the clarity of respiratory signals. The LMS algorithm, established by Widrow and Hoff, is commonly used to perform noise cancellation. After the design and implementation of the LMS algorithm, the project inputted a simulated signal into the adaptive noise cancellation algorithm and managed to output a clean signal. This project will present on the development and implementation of the LMS algorithm on MATLAB to remove undesired noises to get a clearer and cleaner signal. The results and findings will also be discussed. This algorithm will be able to aid doctors in providing a more accurate examination of a patient’s lung health. Bachelor of Engineering (Electrical and Electronic Engineering) 2020-05-18T06:14:49Z 2020-05-18T06:14:49Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/139233 en application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Bioengineering
spellingShingle Engineering::Bioengineering
Soh, Marianne Hui Ying
Noise cancellation algorithm for respiratory sound classification
description The lung is an important organ and an important health indicator of a human. Respiratory diseases are one of the top causes of death and disabilities in the world [1]. It has therefore become vital that the doctor is able to properly diagnose the lung health of a patient as more people go to the clinics and hospitals for their health check ups. Lung sounds such as wheezing and crackling indicates the presence of lung disease. With background noises and interferences, the doctor may not be able to give an accurate examination of the patient’s health. An adaptive filter has self-adjusting characteristics and adapts to changes in its input signals automatically. The objective of this project is to design an adaptive noise cancellation algorithm based on least mean square (LMS) filtering on MATLAB to improve the clarity of respiratory signals. The LMS algorithm, established by Widrow and Hoff, is commonly used to perform noise cancellation. After the design and implementation of the LMS algorithm, the project inputted a simulated signal into the adaptive noise cancellation algorithm and managed to output a clean signal. This project will present on the development and implementation of the LMS algorithm on MATLAB to remove undesired noises to get a clearer and cleaner signal. The results and findings will also be discussed. This algorithm will be able to aid doctors in providing a more accurate examination of a patient’s lung health.
author2 Ser Wee
author_facet Ser Wee
Soh, Marianne Hui Ying
format Final Year Project
author Soh, Marianne Hui Ying
author_sort Soh, Marianne Hui Ying
title Noise cancellation algorithm for respiratory sound classification
title_short Noise cancellation algorithm for respiratory sound classification
title_full Noise cancellation algorithm for respiratory sound classification
title_fullStr Noise cancellation algorithm for respiratory sound classification
title_full_unstemmed Noise cancellation algorithm for respiratory sound classification
title_sort noise cancellation algorithm for respiratory sound classification
publisher Nanyang Technological University
publishDate 2020
url https://hdl.handle.net/10356/139233
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