Data partitioning based weighted averaging for noise suppression in biomedical signals

• Autorzy: Momot A. , Jezewski J. , Wrobel J.
• Języki publikacji: EN

Abstrakty

EN

In the case of biomedical signals with a quasi-cyclic character, such as electrocardiographic signals, the high resolution electrocardiograms or electrical potentials recorded from the nervous system of patients (estimating brain activity evoked by a known stimulus), as a method of averaging in the time domain may be used for noise attenuation. In this paper there is presented input data partitioning applied to a few different methods of weighted averaging. This procedure usually leads to improve the quality of the resulting averaged signal, especially when fuzzy partitioning is used. Below it is presented the computational study of weighted averaging with traditional (sharp) and fuzzy partition of the input data in the presence of non-stationary noise. The performance of presented methods is experimentally evaluated for analytical signal of EN 60601-2-51 (2003), namely ANE20000 ECG record.

Słowa kluczowe

EN

weighted averaging; noise attenuation; quasi-cyclic biomedical signal

PL

ważone uśrednianie; tłumienie hałasu

• Wydawca: University of Silesia, Institute of Informatics, Computer Systems Department
• Czasopismo: Journal of Medical Informatics & Technologies
• Rocznik: 2012
• Tom: Vol. 20
• Strony: 85--91
• Opis fizyczny: Bibliogr. 21 poz., rys.

Twórcy

autor

Momot A.

• Silesian University of Technology, Institute of Informatics, Akademicka St. 16, 44-100 Gliwice

autor

Jezewski J.

autor

Wrobel J.

Bibliografia

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