Analytical view of de-noising methods in ECG signals
Journal Title: International Journal of Research in Computer and Communication Technology - Year 2012, Vol 1, Issue 5
Abstract
This paper deals with the study of ECG signals signal energy, information entropy and joint entropy were analyzed to introduce general selective method of wavelet basis function, and these methods was applied in slow wave diagnosis of electrogastrogram (EGG). In real time acquisition and transmission of the ECG may contain noise signals superimposed on it. In general, the signal processing algorithms employed for denoising provide optimal performance and eliminate the high frequency noise between any two beats contained in a continuous ECG signal. The ECG signal was denoised by removing the corresponding wavelet coefficients at higher scales. Then QRS complexes were detected and each complex was used to find the peaks of the individual waves like P and T, and also their deviations. Power spectrum of EGG was used to prove the effectiveness of selective method of wavelet basis function, and effective selection criteria were also provided to select wavelet basis function in wavelet transform.
Authors and Affiliations
Aaushi Kumari, Megha Bisht
Keywords
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