个人信息Personal Information
教授
博士生导师
硕士生导师
性别:女
毕业院校:大连理工大学
学位:博士
所在单位:信息与通信工程学院
学科:信号与信息处理
联系方式:84706002-3326; 84706697
电子邮箱:qhlin@dlut.edu.cn
Application of the empirical mode decomposition to the analysis of esophageal manometric data in gastroesophageal reflux disease
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论文类型:期刊论文
发表时间:2005-10-01
发表刊物:IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
收录刊物:SCIE、EI、Scopus
卷号:52
期号:10
页面范围:1692-1701
ISSN号:0018-9294
关键字:empirical mode decomposition; esophageal motility; gastroesophageal reflux disease; lower esophageal sphincter
摘要: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.