DocumentCode :
3203541
Title :
Best Wavelet Function Identification System for ECG signal denoise applications
Author :
Tan, H.G.R. ; Tan, A.C. ; Khong, P.Y. ; Mok, V.H.
Author_Institution :
Univ. Coll. Sedaya Int., Kuala Lumpur
fYear :
2007
fDate :
25-28 Nov. 2007
Firstpage :
631
Lastpage :
634
Abstract :
The best wavelet function identification (BestWaveID) system was developed to identify and to select the wavelet function that is optimum to denoise a given ECG signal. Currently the wavelet function identification and selection process are highly rely on human expertise and knowledge of wavelet function in the field of biomedical signal denoising, others rely on trial and error basis which is time consuming. The BestWaveID system require only two inputs to perform the wavelet function evaluation, identification and selection, there are the sample of the ECG signal to be denoise and the expected noise level to be contaminated in the ECG signal. The BestWaveID system perform an iterative denoising on the given ECG signal using every single wavelet function and possible decomposition to evaluate their denoise performance on the given ECG signal in term of signal to noise ratio. The wavelet function that gives the highest signal to noise ratio with the highest occurrence is the optimum denoise wavelet function for the given ECG signal.
Keywords :
electrocardiography; medical signal processing; signal denoising; wavelet transforms; BestWaveID system; ECG signal denoising; biomedical signal denoising; iterative denoising; wavelet function identification system; Discrete wavelet transforms; Electrocardiography; Heart; Noise reduction; Performance evaluation; Signal analysis; Signal denoising; Signal processing; Signal to noise ratio; Wavelet domain; Best Wavelet Function; ECG Denoise; Wavelet Denoise; Wavelet function;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent and Advanced Systems, 2007. ICIAS 2007. International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4244-1355-3
Electronic_ISBN :
978-1-4244-1356-0
Type :
conf
DOI :
10.1109/ICIAS.2007.4658464
Filename :
4658464
Link To Document :
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