A portable device for detecting excessive water in lungs

Pulmonary edema (excessive water in lungs) can cause pulmonary hypertension, pleural effusion and acute case can be fatal. Currently excessive water in lungs is detected by medical devices using X-ray, CT scan or serum biomarker. Previous research works showed that acoustic method with machine learn...

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Bibliographic Details
Main Author: Tang, Yun
Other Authors: Ser Wee
Format: Final Year Project (FYP)
Language:English
Published: 2016
Subjects:
Online Access:http://hdl.handle.net/10356/67630
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author Tang, Yun
author2 Ser Wee
author_facet Ser Wee
Tang, Yun
author_sort Tang, Yun
collection NTU
description Pulmonary edema (excessive water in lungs) can cause pulmonary hypertension, pleural effusion and acute case can be fatal. Currently excessive water in lungs is detected by medical devices using X-ray, CT scan or serum biomarker. Previous research works showed that acoustic method with machine learning algorithms can be applied. This project aimed to implement the previous machine learning algorithms using acoustic models on Android platforms. Because Android smart phones claim huge proportion of smartphone market and most of them are capable of signal real-time processing. During the project, Matlab scripts and a Perl script were written to prepare training data for Android application. Three-level Haar wavelet transform was used for feature extraction of lung sound recordings and kth-nearest-neighbor was used for classification in machine learning section. An Android Application was built for algorithm testing and real-time processing.
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spelling ntu-10356/676302023-07-07T16:19:56Z A portable device for detecting excessive water in lungs Tang, Yun Ser Wee School of Electrical and Electronic Engineering DRNTU::Engineering Pulmonary edema (excessive water in lungs) can cause pulmonary hypertension, pleural effusion and acute case can be fatal. Currently excessive water in lungs is detected by medical devices using X-ray, CT scan or serum biomarker. Previous research works showed that acoustic method with machine learning algorithms can be applied. This project aimed to implement the previous machine learning algorithms using acoustic models on Android platforms. Because Android smart phones claim huge proportion of smartphone market and most of them are capable of signal real-time processing. During the project, Matlab scripts and a Perl script were written to prepare training data for Android application. Three-level Haar wavelet transform was used for feature extraction of lung sound recordings and kth-nearest-neighbor was used for classification in machine learning section. An Android Application was built for algorithm testing and real-time processing. Bachelor of Engineering 2016-05-18T08:29:46Z 2016-05-18T08:29:46Z 2016 Final Year Project (FYP) http://hdl.handle.net/10356/67630 en Nanyang Technological University 64 p. application/pdf
spellingShingle DRNTU::Engineering
Tang, Yun
A portable device for detecting excessive water in lungs
title A portable device for detecting excessive water in lungs
title_full A portable device for detecting excessive water in lungs
title_fullStr A portable device for detecting excessive water in lungs
title_full_unstemmed A portable device for detecting excessive water in lungs
title_short A portable device for detecting excessive water in lungs
title_sort portable device for detecting excessive water in lungs
topic DRNTU::Engineering
url http://hdl.handle.net/10356/67630
work_keys_str_mv AT tangyun aportabledevicefordetectingexcessivewaterinlungs
AT tangyun portabledevicefordetectingexcessivewaterinlungs