Monitoring and alerting system for sleep apnea patients

Obstructive Sleep Apnea (OSA) is a very common sleep disorder which affects a significant portion of the population. The gold standard for monitoring OSA, and the treatment efficacy is through a Polysomnogram (PSG). A PSG measures a multitude of biological signals to determine the severity of OSA. H...

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Main Author: Mohamed Feroz Mohamed Iqubal
Other Authors: Yvonne Lam Ying Hung
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2021
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Online Access:https://hdl.handle.net/10356/149169
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1491692023-07-07T17:41:35Z Monitoring and alerting system for sleep apnea patients Mohamed Feroz Mohamed Iqubal Yvonne Lam Ying Hung School of Electrical and Electronic Engineering EYHLAM@ntu.edu.sg Engineering::Electrical and electronic engineering Obstructive Sleep Apnea (OSA) is a very common sleep disorder which affects a significant portion of the population. The gold standard for monitoring OSA, and the treatment efficacy is through a Polysomnogram (PSG). A PSG measures a multitude of biological signals to determine the severity of OSA. However, a PSG is expensive, and causes discomfort for the patients. The system developed in the first phase of this project allows for home-based monitoring of OSA that is affordable and much more comfortable for the patient than the conventional PSG. It makes use of 3 biological signals, including a single channel frontal electroencephalogram (EEG) from the FP2-A1 positions, blood oxygen saturation (SpO2) reading, and recording of snores. In this system, every individual event is logged into a locally stored file, and if there are at least 2 OSA events happening at the same time, the OSA episode is deemed serious, and a buzzer will sound to wake the patient. A message is also sent to the caregiver / next-of-kin to notify them. The second part of the project focuses on a prediction algorithm, making use of a machine learning technique called k-nearest neighbours, to predict the onset of OSA. With such a prediction algorithm, it is possible to aid treatment techniques such as regulating airflow in the Continuous Positive Airway Pressure (CPAP) treatment. Bachelor of Engineering (Electrical and Electronic Engineering) 2021-05-27T12:13:08Z 2021-05-27T12:13:08Z 2021 Final Year Project (FYP) Mohamed Feroz Mohamed Iqubal (2021). Monitoring and alerting system for sleep apnea patients. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/149169 https://hdl.handle.net/10356/149169 en A2275 - 201 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
spellingShingle Engineering::Electrical and electronic engineering
Mohamed Feroz Mohamed Iqubal
Monitoring and alerting system for sleep apnea patients
description Obstructive Sleep Apnea (OSA) is a very common sleep disorder which affects a significant portion of the population. The gold standard for monitoring OSA, and the treatment efficacy is through a Polysomnogram (PSG). A PSG measures a multitude of biological signals to determine the severity of OSA. However, a PSG is expensive, and causes discomfort for the patients. The system developed in the first phase of this project allows for home-based monitoring of OSA that is affordable and much more comfortable for the patient than the conventional PSG. It makes use of 3 biological signals, including a single channel frontal electroencephalogram (EEG) from the FP2-A1 positions, blood oxygen saturation (SpO2) reading, and recording of snores. In this system, every individual event is logged into a locally stored file, and if there are at least 2 OSA events happening at the same time, the OSA episode is deemed serious, and a buzzer will sound to wake the patient. A message is also sent to the caregiver / next-of-kin to notify them. The second part of the project focuses on a prediction algorithm, making use of a machine learning technique called k-nearest neighbours, to predict the onset of OSA. With such a prediction algorithm, it is possible to aid treatment techniques such as regulating airflow in the Continuous Positive Airway Pressure (CPAP) treatment.
author2 Yvonne Lam Ying Hung
author_facet Yvonne Lam Ying Hung
Mohamed Feroz Mohamed Iqubal
format Final Year Project
author Mohamed Feroz Mohamed Iqubal
author_sort Mohamed Feroz Mohamed Iqubal
title Monitoring and alerting system for sleep apnea patients
title_short Monitoring and alerting system for sleep apnea patients
title_full Monitoring and alerting system for sleep apnea patients
title_fullStr Monitoring and alerting system for sleep apnea patients
title_full_unstemmed Monitoring and alerting system for sleep apnea patients
title_sort monitoring and alerting system for sleep apnea patients
publisher Nanyang Technological University
publishDate 2021
url https://hdl.handle.net/10356/149169
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