Journal article
Application of the empirical mode decomposition to the analysis of esophageal manometric data in gastroesophageal reflux disease
IEEE transactions on biomedical engineering, v 52(10), pp 1692-1701
Oct 2005
PMID: 16235655
Abstract
The Empirical Mode Decomposition (EMD) is a general signal processing method for analyzing nonlinear and nonstationary 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. In this contribution, we applied the idea of EMD to develop strategies to automatically identify the relevant IMFs that contribute to the slow-varying trend in the data, and presented its application on the analysis of esophageal manometric time series in gastroesophageal reflux disease. The results from both extensive simulations and real data show that the EMD may prove to be a vital technique for the analysis of esophageal manometric data.
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Details
- Title
- Application of the empirical mode decomposition to the analysis of esophageal manometric data in gastroesophageal reflux disease
- Creators
- Hualou Liang - School of Health Information Sciences, University of Texas at Houston, 7000 Fannin, Suite 600, Houston, TX 77030, USA. hualou.liang@uth.tmc.eduQiu-Hua LinJ D Z Chen
- Publication Details
- IEEE transactions on biomedical engineering, v 52(10), pp 1692-1701
- Publisher
- The Institute of Electrical and Electronics Engineers, Inc. (IEEE); United States
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- School of Biomedical Engineering, Science, and Health Systems
- Web of Science ID
- WOS:000232116600008
- Scopus ID
- 2-s2.0-20644455171
- Other Identifier
- 991014878101804721
InCites Highlights
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Engineering, Biomedical