Pulse oximeter for blood pressure estimation

Heart diseases are increasingly prominent in mortality rates. Blood pressure is an indicator for the coronary heart disease which is the prime type of heart disease. Blood pressure readings vary based on various conditions. There are multiple methods in finding the blood pressure levels. However, th...

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Main Author: Vijay Tamilselvam
Other Authors: Saman S. Abeysekera
Format: Final Year Project
Language:English
Published: 2019
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Online Access:http://hdl.handle.net/10356/78326
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-783262023-07-07T15:56:28Z Pulse oximeter for blood pressure estimation Vijay Tamilselvam Saman S. Abeysekera School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Heart diseases are increasingly prominent in mortality rates. Blood pressure is an indicator for the coronary heart disease which is the prime type of heart disease. Blood pressure readings vary based on various conditions. There are multiple methods in finding the blood pressure levels. However, these are often traditional method which requires medical professionals’ aid. One of which includes the pulse oximeter whereby it employs Photoplethysmogramic technique to extract multiple useful physiological parameters. Pulse oximeter operates in 2 modes – transmission and reflectance mode. Due to advancements in technology, mobile devices utilise the reflectance mode to yield Photoplethysmogramic signals (PPG) giving heart rate readings. PPG can also be implemented to estimate blood pressure readings by relating the peak values to that of pulse wave velocity, another indicator of blood pressure. However, there are no simple direct methods to extract obtained PPG signal waveforms from these mobile devices to be analysed to yield blood pressure readings. Therefore, this project synthesizes a unique image processing method to extract important features from PPG signal data originating from mobile devices. MATLAB was primarily used as the means of data processing platform. The general trend of various conditions affecting the blood pressure levels were also analysed. Lastly, this project involves itself in deriving a unique general formula relating image data information to that of blood pressure readings. The derived formula was promising as it successfully estimated blood pressure readings as validated by a blood pressure monitor with absolute difference percentage of less than 5%. Bachelor of Engineering (Electrical and Electronic Engineering) 2019-06-18T02:58:08Z 2019-06-18T02:58:08Z 2019 Final Year Project (FYP) http://hdl.handle.net/10356/78326 en Nanyang Technological University 150 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
Vijay Tamilselvam
Pulse oximeter for blood pressure estimation
description Heart diseases are increasingly prominent in mortality rates. Blood pressure is an indicator for the coronary heart disease which is the prime type of heart disease. Blood pressure readings vary based on various conditions. There are multiple methods in finding the blood pressure levels. However, these are often traditional method which requires medical professionals’ aid. One of which includes the pulse oximeter whereby it employs Photoplethysmogramic technique to extract multiple useful physiological parameters. Pulse oximeter operates in 2 modes – transmission and reflectance mode. Due to advancements in technology, mobile devices utilise the reflectance mode to yield Photoplethysmogramic signals (PPG) giving heart rate readings. PPG can also be implemented to estimate blood pressure readings by relating the peak values to that of pulse wave velocity, another indicator of blood pressure. However, there are no simple direct methods to extract obtained PPG signal waveforms from these mobile devices to be analysed to yield blood pressure readings. Therefore, this project synthesizes a unique image processing method to extract important features from PPG signal data originating from mobile devices. MATLAB was primarily used as the means of data processing platform. The general trend of various conditions affecting the blood pressure levels were also analysed. Lastly, this project involves itself in deriving a unique general formula relating image data information to that of blood pressure readings. The derived formula was promising as it successfully estimated blood pressure readings as validated by a blood pressure monitor with absolute difference percentage of less than 5%.
author2 Saman S. Abeysekera
author_facet Saman S. Abeysekera
Vijay Tamilselvam
format Final Year Project
author Vijay Tamilselvam
author_sort Vijay Tamilselvam
title Pulse oximeter for blood pressure estimation
title_short Pulse oximeter for blood pressure estimation
title_full Pulse oximeter for blood pressure estimation
title_fullStr Pulse oximeter for blood pressure estimation
title_full_unstemmed Pulse oximeter for blood pressure estimation
title_sort pulse oximeter for blood pressure estimation
publishDate 2019
url http://hdl.handle.net/10356/78326
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