ST Segment Extraction from Exercise ECG Signal Based on EMD and Wavelet Transform

Myocardial ischemia is always characterized by the changes in ST complex. But ischemia is not obvious at rest. Only in the state of exercise, abnormal ST will appear. The signal of ST is susceptible to noise interference which causes the inaccuracy of the ST segment detection. Combining the advantag...

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Bibliographic Details
Main Authors: You Jia, Jiang Kai, Chen Hang, Wen Haoxiang
Format: Article
Language:English
Published: EDP Sciences 2015-01-01
Series:MATEC Web of Conferences
Subjects:
Online Access:http://dx.doi.org/10.1051/matecconf/20152201039
Description
Summary:Myocardial ischemia is always characterized by the changes in ST complex. But ischemia is not obvious at rest. Only in the state of exercise, abnormal ST will appear. The signal of ST is susceptible to noise interference which causes the inaccuracy of the ST segment detection. Combining the advantages of empirical mode decomposition (EMD), the paper proposes a modified threshold method to filter a serious of noise from exercise ECG. Extracted from the ECG feature, it includes ST segment detection, with wavelet transform. In the end, the method is tested with synthetic exercise data and real exercise ECG data. The results of ST segment detection are accurate and this method can be applied in practical exercise.
ISSN:2261-236X