The Estimation of A Dynamical Mean for Arterial Blood Pressure

碩士 === 逢甲大學 === 自動控制工程所 === 97 === On the contrary, the dynamic mean used in the nonlinear and non-stationary signals is other than the usually average mean obtained from a stationary period. Biomedical signals such as blood pressure and ECG, etc. are typical non-stationary signals. It can’t be trea...

Full description

Bibliographic Details
Main Authors: Pin-huang Hsu, 許炳煌
Other Authors: Chin-yuh Lin
Format: Others
Language:zh-TW
Published: 2009
Online Access:http://ndltd.ncl.edu.tw/handle/78884947081635321043
id ndltd-TW-097FCU05146027
record_format oai_dc
spelling ndltd-TW-097FCU051460272015-11-13T04:15:05Z http://ndltd.ncl.edu.tw/handle/78884947081635321043 The Estimation of A Dynamical Mean for Arterial Blood Pressure 即時脈壓動態平均值之估測 Pin-huang Hsu 許炳煌 碩士 逢甲大學 自動控制工程所 97 On the contrary, the dynamic mean used in the nonlinear and non-stationary signals is other than the usually average mean obtained from a stationary period. Biomedical signals such as blood pressure and ECG, etc. are typical non-stationary signals. It can’t be treated as average mean of the stationary calculation. The dynamic mean may be defined as the average of the maximum and minimum at instant time. It could be found by using Empirical Mode Decomposition(EMD) developed by Norden E. Huang. However, it isn’t eligible to compute the dynamic mean in real time. The purpose of this paper is to propose a technique that combines EMD, pattern recognition, estimation and prediction theory, estimating the real time dynamic means effectively. From ten healthy subjects(20~28 years old) the simulation results reveal that the mean errors were less than 1 mmHg and indicates that the on-line estimation of dynamic mean blood pressure is feasible. Chin-yuh Lin 林欽裕 2009 學位論文 ; thesis 45 zh-TW
collection NDLTD
language zh-TW
format Others
sources NDLTD
description 碩士 === 逢甲大學 === 自動控制工程所 === 97 === On the contrary, the dynamic mean used in the nonlinear and non-stationary signals is other than the usually average mean obtained from a stationary period. Biomedical signals such as blood pressure and ECG, etc. are typical non-stationary signals. It can’t be treated as average mean of the stationary calculation. The dynamic mean may be defined as the average of the maximum and minimum at instant time. It could be found by using Empirical Mode Decomposition(EMD) developed by Norden E. Huang. However, it isn’t eligible to compute the dynamic mean in real time. The purpose of this paper is to propose a technique that combines EMD, pattern recognition, estimation and prediction theory, estimating the real time dynamic means effectively. From ten healthy subjects(20~28 years old) the simulation results reveal that the mean errors were less than 1 mmHg and indicates that the on-line estimation of dynamic mean blood pressure is feasible.
author2 Chin-yuh Lin
author_facet Chin-yuh Lin
Pin-huang Hsu
許炳煌
author Pin-huang Hsu
許炳煌
spellingShingle Pin-huang Hsu
許炳煌
The Estimation of A Dynamical Mean for Arterial Blood Pressure
author_sort Pin-huang Hsu
title The Estimation of A Dynamical Mean for Arterial Blood Pressure
title_short The Estimation of A Dynamical Mean for Arterial Blood Pressure
title_full The Estimation of A Dynamical Mean for Arterial Blood Pressure
title_fullStr The Estimation of A Dynamical Mean for Arterial Blood Pressure
title_full_unstemmed The Estimation of A Dynamical Mean for Arterial Blood Pressure
title_sort estimation of a dynamical mean for arterial blood pressure
publishDate 2009
url http://ndltd.ncl.edu.tw/handle/78884947081635321043
work_keys_str_mv AT pinhuanghsu theestimationofadynamicalmeanforarterialbloodpressure
AT xǔbǐnghuáng theestimationofadynamicalmeanforarterialbloodpressure
AT pinhuanghsu jíshímàiyādòngtàipíngjūnzhízhīgūcè
AT xǔbǐnghuáng jíshímàiyādòngtàipíngjūnzhízhīgūcè
AT pinhuanghsu estimationofadynamicalmeanforarterialbloodpressure
AT xǔbǐnghuáng estimationofadynamicalmeanforarterialbloodpressure
_version_ 1718129646112866304