Respiratory sound analysis : noise suppression techniques

Respiratory sound signal is the signal generated by the respiratory system. It contains information of respiratory system and can be used to monitor the condition of the system. However, the process of recording respiratory signals will introduce noise from all sources. It is essential to filter the...

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Main Author: Ge, Yihui
Other Authors: Ser Wee
Format: Thesis-Master by Coursework
Language:English
Published: Nanyang Technological University 2020
Subjects:
Online Access:https://hdl.handle.net/10356/142932
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1429322023-07-04T15:04:00Z Respiratory sound analysis : noise suppression techniques Ge, Yihui Ser Wee School of Electrical and Electronic Engineering Bioinformatics Research Centre ewser@ntu.edu.sg Engineering::Electrical and electronic engineering::Electronic systems::Signal processing Respiratory sound signal is the signal generated by the respiratory system. It contains information of respiratory system and can be used to monitor the condition of the system. However, the process of recording respiratory signals will introduce noise from all sources. It is essential to filter the noise because it will affect the precision of medical diagnosis. This paper analyzes the composition of the noise and proposes solutions to eliminate noise accordingly. In this paper, a denoising system based on the technique of digital filters and adaptive filter is designed to remove the unwanted noise components from the original signal. The system consists of two parts, processing with digital filters, and adaptive filters. The result of the system is analyzed, and the performance of the system is evaluated in this paper. Due to the experiments, the processing with digital filters removes the most of noise components and improves the quality of signal greatly, and the rest of the noise can be removed with adaptive filters. RLS has better performance and faster speed of convergence compared with LMS in denoising respiratory signals. Master of Science (Signal Processing) 2020-07-14T02:02:57Z 2020-07-14T02:02:57Z 2020 Thesis-Master by Coursework https://hdl.handle.net/10356/142932 en ISM-DISS-02008 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::Electrical and electronic engineering::Electronic systems::Signal processing
spellingShingle Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Ge, Yihui
Respiratory sound analysis : noise suppression techniques
description Respiratory sound signal is the signal generated by the respiratory system. It contains information of respiratory system and can be used to monitor the condition of the system. However, the process of recording respiratory signals will introduce noise from all sources. It is essential to filter the noise because it will affect the precision of medical diagnosis. This paper analyzes the composition of the noise and proposes solutions to eliminate noise accordingly. In this paper, a denoising system based on the technique of digital filters and adaptive filter is designed to remove the unwanted noise components from the original signal. The system consists of two parts, processing with digital filters, and adaptive filters. The result of the system is analyzed, and the performance of the system is evaluated in this paper. Due to the experiments, the processing with digital filters removes the most of noise components and improves the quality of signal greatly, and the rest of the noise can be removed with adaptive filters. RLS has better performance and faster speed of convergence compared with LMS in denoising respiratory signals.
author2 Ser Wee
author_facet Ser Wee
Ge, Yihui
format Thesis-Master by Coursework
author Ge, Yihui
author_sort Ge, Yihui
title Respiratory sound analysis : noise suppression techniques
title_short Respiratory sound analysis : noise suppression techniques
title_full Respiratory sound analysis : noise suppression techniques
title_fullStr Respiratory sound analysis : noise suppression techniques
title_full_unstemmed Respiratory sound analysis : noise suppression techniques
title_sort respiratory sound analysis : noise suppression techniques
publisher Nanyang Technological University
publishDate 2020
url https://hdl.handle.net/10356/142932
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