Artefact detection for improved processing of pulse oximeter signals

Photoplethysmography (PPG) signal which is produced from the Pulse Oximeter can be used for many clinical medication like Heart rate (HR), Blood pressure, Oxygen saturation (Sp02) and Heart rate Variability (HRV). Hence, Pulse Oximetry has become an essential medical device which is commonly used i...

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Main Author: Wong, Poi Kuan
Other Authors: Saman S. Abeysekera
Format: Final Year Project
Language:English
Published: 2018
Subjects:
Online Access:http://hdl.handle.net/10356/74962
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-749622023-07-07T16:29:43Z Artefact detection for improved processing of pulse oximeter signals Wong, Poi Kuan Saman S. Abeysekera School of Electrical and Electronic Engineering DRNTU::Engineering Photoplethysmography (PPG) signal which is produced from the Pulse Oximeter can be used for many clinical medication like Heart rate (HR), Blood pressure, Oxygen saturation (Sp02) and Heart rate Variability (HRV). Hence, Pulse Oximetry has become an essential medical device which is commonly used in hospitals and clinics to monitor patient with asthma, Chronic Obstructive Pulmonary disease (COPD), and other respiratory issues [1]. However, Pulse Oximeter is prone to varieties of artefacts interferences which will produce inaccurate result. Therefore, this report will discuss the on the methodology to remove the motion artefacts and other interferences that will corrupt the PPG signal. The clean PPG signal will then use for evaluating physiologically important parameters. In the project development, existed Pulse Oximeter circuit is provided for Photoplethysmography (PPG) signal collection. LabVIEW is used to visualise the real time analysis of the PPG signal and NI DAQ card will subsequently convert the signal in to excel format and transfer to MATLAB for further processing and analysis. Bachelor of Engineering 2018-05-25T05:27:23Z 2018-05-25T05:27:23Z 2018 Final Year Project (FYP) http://hdl.handle.net/10356/74962 en Nanyang Technological University 71 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
spellingShingle DRNTU::Engineering
Wong, Poi Kuan
Artefact detection for improved processing of pulse oximeter signals
description Photoplethysmography (PPG) signal which is produced from the Pulse Oximeter can be used for many clinical medication like Heart rate (HR), Blood pressure, Oxygen saturation (Sp02) and Heart rate Variability (HRV). Hence, Pulse Oximetry has become an essential medical device which is commonly used in hospitals and clinics to monitor patient with asthma, Chronic Obstructive Pulmonary disease (COPD), and other respiratory issues [1]. However, Pulse Oximeter is prone to varieties of artefacts interferences which will produce inaccurate result. Therefore, this report will discuss the on the methodology to remove the motion artefacts and other interferences that will corrupt the PPG signal. The clean PPG signal will then use for evaluating physiologically important parameters. In the project development, existed Pulse Oximeter circuit is provided for Photoplethysmography (PPG) signal collection. LabVIEW is used to visualise the real time analysis of the PPG signal and NI DAQ card will subsequently convert the signal in to excel format and transfer to MATLAB for further processing and analysis.
author2 Saman S. Abeysekera
author_facet Saman S. Abeysekera
Wong, Poi Kuan
format Final Year Project
author Wong, Poi Kuan
author_sort Wong, Poi Kuan
title Artefact detection for improved processing of pulse oximeter signals
title_short Artefact detection for improved processing of pulse oximeter signals
title_full Artefact detection for improved processing of pulse oximeter signals
title_fullStr Artefact detection for improved processing of pulse oximeter signals
title_full_unstemmed Artefact detection for improved processing of pulse oximeter signals
title_sort artefact detection for improved processing of pulse oximeter signals
publishDate 2018
url http://hdl.handle.net/10356/74962
_version_ 1772827280023748608