Effect of sensor type to respiratory sound classification

Commonly known as “water in the lungs”, pulmonary edema is a respiratory condition caused by excess fluid build-up in air sacs of the lungs. It is often caused by congestive heart failure (CHF). As such, pulmonary edema is an indicative sign that a patient’s health condition is at risk, since CHF is...

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Main Author: Kan, Debbie Siew Yin
Other Authors: Ser Wee
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2020
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Online Access:https://hdl.handle.net/10356/138698
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Institution: Nanyang Technological University
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spelling sg-ntu-dr.10356-1386982023-07-07T18:15:53Z Effect of sensor type to respiratory sound classification Kan, Debbie Siew Yin Ser Wee School of Electrical and Electronic Engineering ewser@ntu.edu.sg Engineering Commonly known as “water in the lungs”, pulmonary edema is a respiratory condition caused by excess fluid build-up in air sacs of the lungs. It is often caused by congestive heart failure (CHF). As such, pulmonary edema is an indicative sign that a patient’s health condition is at risk, since CHF is not a condition to easily diagnose. The shortness of breath arising from pulmonary edema can lead to severe health risks if failed to be diagnosed early or left untreated. Although X-rays and computed tomography (CT) scans can detect water presence in the lungs, these methods are expensive and bulky, thus not easily made available to everyone. The aim of this project is to study and analyse the performances of three systems in classification of water presence in the lungs. This would be done using audio samples collected from using the systems on actual patients at Tan Tock Seng Hospital and from professional opinion of the patients’ health status. The analysis would be conducted based on 3 metrics – accuracy, sensitivity and specificity. From the analysis, both qualitative and quantitative results have shown that all three systems are relatively accurate with a minimum classification accuracy of around 80%. However, the superior system is System 2, where it has the most consistent performance with high levels of aforementioned metrics of around 98%. Bachelor of Engineering (Electrical and Electronic Engineering) 2020-05-12T02:31:31Z 2020-05-12T02:31:31Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/138698 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
spellingShingle Engineering
Kan, Debbie Siew Yin
Effect of sensor type to respiratory sound classification
description Commonly known as “water in the lungs”, pulmonary edema is a respiratory condition caused by excess fluid build-up in air sacs of the lungs. It is often caused by congestive heart failure (CHF). As such, pulmonary edema is an indicative sign that a patient’s health condition is at risk, since CHF is not a condition to easily diagnose. The shortness of breath arising from pulmonary edema can lead to severe health risks if failed to be diagnosed early or left untreated. Although X-rays and computed tomography (CT) scans can detect water presence in the lungs, these methods are expensive and bulky, thus not easily made available to everyone. The aim of this project is to study and analyse the performances of three systems in classification of water presence in the lungs. This would be done using audio samples collected from using the systems on actual patients at Tan Tock Seng Hospital and from professional opinion of the patients’ health status. The analysis would be conducted based on 3 metrics – accuracy, sensitivity and specificity. From the analysis, both qualitative and quantitative results have shown that all three systems are relatively accurate with a minimum classification accuracy of around 80%. However, the superior system is System 2, where it has the most consistent performance with high levels of aforementioned metrics of around 98%.
author2 Ser Wee
author_facet Ser Wee
Kan, Debbie Siew Yin
format Final Year Project
author Kan, Debbie Siew Yin
author_sort Kan, Debbie Siew Yin
title Effect of sensor type to respiratory sound classification
title_short Effect of sensor type to respiratory sound classification
title_full Effect of sensor type to respiratory sound classification
title_fullStr Effect of sensor type to respiratory sound classification
title_full_unstemmed Effect of sensor type to respiratory sound classification
title_sort effect of sensor type to respiratory sound classification
publisher Nanyang Technological University
publishDate 2020
url https://hdl.handle.net/10356/138698
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