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ECG denoise method based on wavelet function learning

Title
ECG denoise method based on wavelet function learning
Authors
Kang, Won-SeokYun, SanghunCho, Kookrae
DGIST Authors
Kang, Won-Seok; Yun, Sanghun; Cho, Kookrae
Issue Date
2012
Citation
11th IEEE SENSORS 2012 Conference
Type
Conference
Article Type
Conference Paper
ISBN
9780000000000
Abstract
In this paper, we propose a new denoise method for noisy electrocardiogram (ECG) signals. We employ an n-gram-based wavelet learning in order to investigate optimal classical wavelet sequences for ECG signals denoise. Our main approach separates the ECG signal of the interest into multi-windows then assigns the optimal wavelet to each window. The wavelet learning approach uses the mean square error(MSE) as a feature to generate an n-gram table. Also, we selected MSE and the signal-to-noise ratio(SNR) for evaluation factors. As a result of simulation, we confirmed that the performance become more precise than the previous approaches. © 2012 IEEE.
URI
http://hdl.handle.net/20.500.11750/3873
DOI
10.1109/ICSENS.2012.6411438
Publisher
Institute of Electrical and Electronics Engineers Inc.
Related Researcher
Files:
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Collection:
Division of IoT∙Robotics Convergence Research2. Conference Papers
Companion Diagnostics and Medical Technology Research Group2. Conference Papers


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