



@conference {2566,
	title = {ECG noise filtering using wavelets with soft-thresholding methods},
	booktitle = {Computers in CardiologyComput Cardiol},
	series = {The 26th Annual Meeting: Computers in Cardiology 1999},
	year = {1999},
	note = {Conference code: 56519Cited By (since 1996): 29Export Date: 21 November 2012Source: ScopusCODEN: COCADLanguage of Original Document: EnglishCorrespondence Address: Agante, P.M.; Inst Nacional de Engenharia, Biomedica, Oporto, PortugalReferences: Graps, A., An introduction to wavelets (1995) IEEE Computational Science and Engineering, 2 (2);Donoho, D.L., De-noising by soft-thresholding (1992) Symposium on Wavelet Theory, , Vanderbilt; 
Daubechies, I., The wavelet transform, time-frequency localization and signal analysis (1990) IEEE Transactions on Information Theory, 36 (5), pp. 961-1005; 
Chui, C.K., (1992) An Introduction to Wavelets, , Academic Press; 
Willems, J.L., CSE multilead atlas (1988) Common Standards for Quantitative Electrocardiography (European Concerted Action Project II.2.2), Div. Medical Informatics, , CSE Project Leader, Univ. Hosp. Gasthuisberg, Leuven; 
Coifman, R., Meyer, Y., Wickerhauser, V., Wavelet Analysis and Signal Processing, , ceres.math.yale.edu, Yale University, available by anonymous ftp at; 
},
	month = {1999///},
	pages = {535 - 538},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Hannover, Ger},
	abstract = {In this paper we analyze algorithms for filtering white gaussian noise and 50 Hz power line noise from ECG signals. We used several wavelets to study their effect and efficiency in the filtering process. To deal with these different kinds of noises we used two distinct soft-thresholding techniques: the Donoho{\textquoteright}s statistical threshold estimator and a method developed by us. This last method exploits one of the wavelet processing main features: time-frequency relation. The de-noising methods led to good filtering results: noise reduction with only minor change of the ECG waveforms as confirmed by the high correlation values between the processed signal and the original one. These good results are due to a wavelet advantage over classical filtering - time-frequency relation - enabling the possibility of filtering noise in the same frequency band of the ECG signal with minimal interference.},
	keywords = {Algorithms, Electrocardiography, Signal filtering and prediction, Signal interference, Wavelet denoising, White noise},
	isbn = {02766574 (ISSN)},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0342854378\&partnerID=40\&md5=11e3b634e77d95bc3486d33a9f2a4b2d},
	author = {Agante Da Silva, P.M.G. and Marques De S{\'a}, J.P.}
}
