Research and Analysis of ECG Signal Feature Detection Based on Multi-Resolution Analysis and Baselines Wander

Hui Yu Yang

doi:10.4028/www.scientific.net/AMR.926-930.1827

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 926-930Research and Analysis of ECG Signal Feature...

Research and Analysis of ECG Signal Feature Detection Based on Multi-Resolution Analysis and Baselines Wander

Abstract:

Electrocardiosignal feature extraction is the base of electrocard iologic automatic diagnosis. By using wavelet transform multi-resolution analysis, the noise in electrocard iosignal is removed; and by using proximity signals of wavelet transform the base linew ander is filtered. The high frequency noise is handled and eliminated with the default threshold; and the average value of the electrocardiosignals is set to zero. In detection of rpeak, because leak detection will occur when only 2³ detail signals is considered, thus the 2³ and 2⁴ detail signals are integrated to avoid miss detection effectively. The methods avoiding error detection bring excellent effects. For calculating average cardiac electric axis, among the methods of area method, time voltage method and amplitude method, the area method offers the highest accuracy.

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Periodical:

Advanced Materials Research (Volumes 926-930)

Pages:

1827-1830

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.926-930.1827

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Online since:

May 2014

Authors:

Hui Yu Yang*

Keywords:

Average Cardiac Electric Axis, Baseline Wander, ECG, Mallat Algorithm, Multi-Resolution Analysis, Wavelet Transform (WT)

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