Online monitoring & classification of blood pressure profiles.

Chinese pulse wave diagnosis had remained a subjective art in Traditional Chinese Medicine(TCM) for over 2000 years, until a recent 2006 study, which developed classification indices of the waveforms. The waveforms were classified based on wave parameters such as the wave length, relative phase diff...

Full description

Saved in:
Bibliographic Details
Main Author: Asoke Kumar Sakthi.
Other Authors: Lim Sierin
Format: Final Year Project
Language:English
Published: 2013
Subjects:
Online Access:http://hdl.handle.net/10356/53919
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-53919
record_format dspace
spelling sg-ntu-dr.10356-539192023-03-03T15:31:48Z Online monitoring & classification of blood pressure profiles. Asoke Kumar Sakthi. Lim Sierin Seet Gim Lee, Gerald School of Chemical and Biomedical Engineering DRNTU::Engineering::Mechanical engineering DRNTU::Engineering::Bioengineering Chinese pulse wave diagnosis had remained a subjective art in Traditional Chinese Medicine(TCM) for over 2000 years, until a recent 2006 study, which developed classification indices of the waveforms. The waveforms were classified based on wave parameters such as the wave length, relative phase difference, rate parameters and peak ratio. Western medicine has started using pulse wave analysis in the past two decades, though only in the field of circulation and cardiovascular diseases. However, the methods of measuring blood pressure have been established for nearly a century. Combining both the Western techniques of blood pressure measurement and Chinese Pulse diagnosis, many researchers have worked to computerize the wave pattern matching and automate the pulse diagnosis process. In this study, we seek to use direct pressure sensing method to obtain the pulse wave and analyze the frequency components of the wave via a Fast Fourier Transform (FFT). The frequency signatures and their amplitudes were studied from the resultant power spectrums. These signatures were then analyzed for patterns to aid in the classification of the different types of waves. Before experimental pulse wave acquisition, existing pulse wave patterns were simulated and analyzed. From the results of this experimental study, the effects of this analysis technique are studied and improvements for further research in this field have been suggested. Bachelor of Engineering (Chemical and Biomolecular Engineering) 2013-06-10T04:23:35Z 2013-06-10T04:23:35Z 2013 2013 Final Year Project (FYP) http://hdl.handle.net/10356/53919 en Nanyang Technological University 73 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::Mechanical engineering
DRNTU::Engineering::Bioengineering
spellingShingle DRNTU::Engineering::Mechanical engineering
DRNTU::Engineering::Bioengineering
Asoke Kumar Sakthi.
Online monitoring & classification of blood pressure profiles.
description Chinese pulse wave diagnosis had remained a subjective art in Traditional Chinese Medicine(TCM) for over 2000 years, until a recent 2006 study, which developed classification indices of the waveforms. The waveforms were classified based on wave parameters such as the wave length, relative phase difference, rate parameters and peak ratio. Western medicine has started using pulse wave analysis in the past two decades, though only in the field of circulation and cardiovascular diseases. However, the methods of measuring blood pressure have been established for nearly a century. Combining both the Western techniques of blood pressure measurement and Chinese Pulse diagnosis, many researchers have worked to computerize the wave pattern matching and automate the pulse diagnosis process. In this study, we seek to use direct pressure sensing method to obtain the pulse wave and analyze the frequency components of the wave via a Fast Fourier Transform (FFT). The frequency signatures and their amplitudes were studied from the resultant power spectrums. These signatures were then analyzed for patterns to aid in the classification of the different types of waves. Before experimental pulse wave acquisition, existing pulse wave patterns were simulated and analyzed. From the results of this experimental study, the effects of this analysis technique are studied and improvements for further research in this field have been suggested.
author2 Lim Sierin
author_facet Lim Sierin
Asoke Kumar Sakthi.
format Final Year Project
author Asoke Kumar Sakthi.
author_sort Asoke Kumar Sakthi.
title Online monitoring & classification of blood pressure profiles.
title_short Online monitoring & classification of blood pressure profiles.
title_full Online monitoring & classification of blood pressure profiles.
title_fullStr Online monitoring & classification of blood pressure profiles.
title_full_unstemmed Online monitoring & classification of blood pressure profiles.
title_sort online monitoring & classification of blood pressure profiles.
publishDate 2013
url http://hdl.handle.net/10356/53919
_version_ 1759852949771649024