Estimation of heart and respiratory rates using pulse oximeters
In this report, algorithm was created to estimate heart rate and respiratory rate using photoplethysmogram (PPG). PPG was acquired from fingertip of human body using pulse sensor amped. The PPG acquired from pulse sensor amped was recorded and save for further processing using MATLAB. PPG signal und...
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sg-ntu-dr.10356-720292023-07-07T15:52:12Z Estimation of heart and respiratory rates using pulse oximeters Yap, Felicia Lii Wen Soh Cheong Boon School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Medical electronics In this report, algorithm was created to estimate heart rate and respiratory rate using photoplethysmogram (PPG). PPG was acquired from fingertip of human body using pulse sensor amped. The PPG acquired from pulse sensor amped was recorded and save for further processing using MATLAB. PPG signal undergo pre-processing stage which include the removal of DC component to have a better waveform for future analysis. To estimate the respiratory rate, three respiratory induced variations which are frequency, amplitude and intensity are extracted from PPG. All three respiratory induced variations are analysed using Fast Fourier Transform (FFT) to get the frequency spectrum of the respiratory induced variations. Respiratory rate can be estimate from the frequency spectrum. Heart rate can be estimate by performing FFT on PPG. From the PPG frequency spectrum, the highest peak value that falls within the heart rate frequency band which is around 0.6Hz to 5Hz is recorded to calculate for heart rate. Bachelor of Engineering 2017-05-23T08:03:21Z 2017-05-23T08:03:21Z 2017 Final Year Project (FYP) http://hdl.handle.net/10356/72029 en Nanyang Technological University 37 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Medical electronics Yap, Felicia Lii Wen Estimation of heart and respiratory rates using pulse oximeters |
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In this report, algorithm was created to estimate heart rate and respiratory rate using photoplethysmogram (PPG). PPG was acquired from fingertip of human body using pulse sensor amped. The PPG acquired from pulse sensor amped was recorded and save for further processing using MATLAB. PPG signal undergo pre-processing stage which include the removal of DC component to have a better waveform for future analysis. To estimate the respiratory rate, three respiratory induced variations which are frequency, amplitude and intensity are extracted from PPG. All three respiratory induced variations are analysed using Fast Fourier Transform (FFT) to get the frequency spectrum of the respiratory induced variations. Respiratory rate can be estimate from the frequency spectrum. Heart rate can be estimate by performing FFT on PPG. From the PPG frequency spectrum, the highest peak value that falls within the heart rate frequency band which is around 0.6Hz to 5Hz is recorded to calculate for heart rate. |
author2 |
Soh Cheong Boon |
author_facet |
Soh Cheong Boon Yap, Felicia Lii Wen |
format |
Final Year Project |
author |
Yap, Felicia Lii Wen |
author_sort |
Yap, Felicia Lii Wen |
title |
Estimation of heart and respiratory rates using pulse oximeters |
title_short |
Estimation of heart and respiratory rates using pulse oximeters |
title_full |
Estimation of heart and respiratory rates using pulse oximeters |
title_fullStr |
Estimation of heart and respiratory rates using pulse oximeters |
title_full_unstemmed |
Estimation of heart and respiratory rates using pulse oximeters |
title_sort |
estimation of heart and respiratory rates using pulse oximeters |
publishDate |
2017 |
url |
http://hdl.handle.net/10356/72029 |
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1772827279460663296 |