Sound based respiratory rate estimation

Respiratory rate serves as an important vital sign to indicate the state of patient’s health. It is often measured to detect early diseases and monitor deteriorations in patients. However, due to the inadequacies of existing methods of respiratory rate measurement, there is a need to develop better...

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Main Author: Lee, Ashley Hui Qing
Other Authors: Ser Wee
Format: Final Year Project
Language:English
Published: 2019
Subjects:
Online Access:http://hdl.handle.net/10356/77995
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-779952023-07-07T16:27:48Z Sound based respiratory rate estimation Lee, Ashley Hui Qing Ser Wee School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Respiratory rate serves as an important vital sign to indicate the state of patient’s health. It is often measured to detect early diseases and monitor deteriorations in patients. However, due to the inadequacies of existing methods of respiratory rate measurement, there is a need to develop better estimation methods for simple and cost-effective monitoring. Recently, there have been more studies on non-invasive measures in the near environment of the patients. Respiratory rate estimation based on sound signals is one area explored. While existing sound based algorithms reflect positive performance, few examined the effect of varied conditions on its performance. The objective of this final year project is to develop a sound based respiratory rate estimation algorithm and study its performance under various conditions to improve its accuracy. The algorithm was evaluated using open source audio samples. The findings of this study revealed strong performance for the algorithm. The correlation coefficient between the estimated and reference respiratory rate is 0.98, with an average percentage accuracy of 95.15% across the test samples. The findings also concluded that the variation of parameters and injection of noise reflected an effect on the algorithm performance. Bachelor of Engineering (Information Engineering and Media) 2019-06-11T01:37:38Z 2019-06-11T01:37:38Z 2019 Final Year Project (FYP) http://hdl.handle.net/10356/77995 en Nanyang Technological University 95 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
Lee, Ashley Hui Qing
Sound based respiratory rate estimation
description Respiratory rate serves as an important vital sign to indicate the state of patient’s health. It is often measured to detect early diseases and monitor deteriorations in patients. However, due to the inadequacies of existing methods of respiratory rate measurement, there is a need to develop better estimation methods for simple and cost-effective monitoring. Recently, there have been more studies on non-invasive measures in the near environment of the patients. Respiratory rate estimation based on sound signals is one area explored. While existing sound based algorithms reflect positive performance, few examined the effect of varied conditions on its performance. The objective of this final year project is to develop a sound based respiratory rate estimation algorithm and study its performance under various conditions to improve its accuracy. The algorithm was evaluated using open source audio samples. The findings of this study revealed strong performance for the algorithm. The correlation coefficient between the estimated and reference respiratory rate is 0.98, with an average percentage accuracy of 95.15% across the test samples. The findings also concluded that the variation of parameters and injection of noise reflected an effect on the algorithm performance.
author2 Ser Wee
author_facet Ser Wee
Lee, Ashley Hui Qing
format Final Year Project
author Lee, Ashley Hui Qing
author_sort Lee, Ashley Hui Qing
title Sound based respiratory rate estimation
title_short Sound based respiratory rate estimation
title_full Sound based respiratory rate estimation
title_fullStr Sound based respiratory rate estimation
title_full_unstemmed Sound based respiratory rate estimation
title_sort sound based respiratory rate estimation
publishDate 2019
url http://hdl.handle.net/10356/77995
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