DocumentCode
2722610
Title
Application of the empirical mode decomposition to the analysis of esophageal manometric data in gastroesophageal reflux disease
Author
Liang, Hualou ; Lin, Qiu-Hua ; Chen, J.D.Z.
Author_Institution
Sch. of Health Inf. Sci., Texas Univ., Houston, TX, USA
Volume
1
fYear
2004
fDate
1-5 Sept. 2004
Firstpage
620
Lastpage
623
Abstract
The empirical mode decomposition (EMD) is a general signal processing method for analyzing nonlinear and non-stationary time series. The central idea of EMD is to decompose a time series into a finite and often small number of intrinsic mode functions (IMFs). An IMF is defined as any function having the number of extrema and the number of zero-crossings equal (or differing at most by one), and also having symmetric envelopes defined by the local minima, and maxima respectively. The decomposition procedure is adaptive, data-driven, therefore, highly efficient The EMD is first described, and its performance is validated by simulations. The EMD is then applied to the analysis of esophageal manometric time series in gastroesophageal reflux disease. The results show that the EMD may prove to be a vital technique for the analysis of esophageal manometric data.
Keywords
biomedical measurement; diseases; manometers; medical signal processing; time series; empirical mode decomposition; esophageal manometric data analysis; gastroesophageal reflux disease; intrinsic mode functions; nonlinear time series; nonstationary time series; signal processing; Back; Cardiac disease; Cardiovascular diseases; Catheters; Esophagus; Muscles; Nose; Pollution measurement; Pressure measurement; Stomach; Empirical mode decomposition; esophageal manometry; gastroesophageal reflux disease; lower esophageal sphincter;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE
Conference_Location
San Francisco, CA
Print_ISBN
0-7803-8439-3
Type
conf
DOI
10.1109/IEMBS.2004.1403234
Filename
1403234
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