Please use this identifier to cite or link to this item: https://ir.swu.ac.th/jspui/handle/123456789/13309
Title: Denoising of electrocardiogram measurement system based on statistical signal processing
Authors: Sueaseenak D.
Keywords: Data acquisition
Diagnosis
Electrocardiography
Independent component analysis
Signal denoising
Signal processing
Signal to noise ratio
Correlation coefficient
De-noising
Design and construction
Electrocardiogram signal
External interference
Independent component analysis(ICA)
Modern signal processing
Statistical signal processing
Biomedical signal processing
Issue Date: 2016
Abstract: Electrocardiogram(ECG) signal is the most important of medical information used to diagnosis and indicates the condition of the heart in humans. In a design and construction of single-lead electrocardiogram measurement system using discrete component incorporated with data acquisition(DAQ) was a problem from the noise or external interference. The modern technology in signals processing used to perform a noise canceling in electrocardiography. In this paper, we propose the simulation study of modern signal processing technique to separate the single channel of ECG signals from noise and others interference. The ECG signal was performed a denoising using ICA. A useful ICA algorithm called FAS-TICA is a highperformance algorithm to divide multiple linear combinations of ECG and noise to statistically independent elements. Our experimental results indicate the robustness of ICA after applied ECG is higher than before applied ICA, since the correlation coefficient and SNR is improved with minimum error. © 2016 IEEE.
URI: https://ir.swu.ac.th/jspui/handle/123456789/13309
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85010379655&doi=10.1109%2fGCCE.2016.7800349&partnerID=40&md5=784b65f2cbce372bf5870f65f2bb40f5
Appears in Collections:Scopus 1983-2021

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