Artículo

Rosso, O.A.; Figliola, A.; Creso, J.; Serrano, E. "Analysis of wavelet-filtered tonic-clonic electroencephalogram recordings" (2004) Medical and Biological Engineering and Computing. 42(4):516-523
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Abstract:

EEG signals obtained during tonic-clonic epileptic seizures can be severely contaminated by muscle and physiological noise. Heavily contaminated EEG signals are hard to analyse quantitatively and also are usually rejected for visual inspection by physicians, resulting in a considerable loss of collected information. The aim of this work was to develop a computer-based method of time series analysis for such EEGs. A method is presented for filtering those frequencies associated with muscle activity using a wavelet transform. One of the advantages of this method over traditional filtering is that wavelet filtering of some frequency bands does not modify the pattern of the remaining ones. In consequence, the dynamics associated with them do not change. After generation of a 'noise free' signal by removal of the muscle artifacts using wavelets, a dynamic analysis was performed using non-linear dynamics metric tools. The characteristic parameters evaluated (correlation dimension D2 and largest Lyapunov exponent λ1) were compatible with those obtained in previous works. The average values obtained were: D2 = 4.25 and λ1=3.27 for the pre-ictal stage, D2=4.03 and λ1=2.68 for the tonic seizure stage, D2=4.11 and λ1=2.46 for the clonic seizure stage. © IFMBE: 2004.

Registro:

Documento: Artículo
Título:Analysis of wavelet-filtered tonic-clonic electroencephalogram recordings
Autor:Rosso, O.A.; Figliola, A.; Creso, J.; Serrano, E.
Filiación:Instituto de Cálculo, Fac. de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
Departamento de Matemáticas, Fac. de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
Palabras clave:EEG; Epileptic seizures; Non-linear dynamics metric tools; Wavelet analysis; Muscle artifacts; Physicians; Physiological noise; Acoustic noise; Biomedical engineering; Information analysis; Muscle; Signal detection; Time series analysis; Electroencephalography; analytic method; analytical parameters; article; artifact; computer analysis; controlled study; correlation analysis; electroencephalogram; filtration; frequency analysis; metric system; muscle contraction; nonlinear system; recording; signal noise ratio; time series analysis; tonic clonic seizure; Artifacts; Electroencephalography; Epilepsy, Tonic-Clonic; Humans; Signal Processing, Computer-Assisted
Año:2004
Volumen:42
Número:4
Página de inicio:516
Página de fin:523
DOI: http://dx.doi.org/10.1007/BF02350993
Título revista:Medical and Biological Engineering and Computing
Título revista abreviado:Med. Biol. Eng. Comput.
ISSN:01400118
CODEN:MBECD
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01400118_v42_n4_p516_Rosso

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Citas:

---------- APA ----------
Rosso, O.A., Figliola, A., Creso, J. & Serrano, E. (2004) . Analysis of wavelet-filtered tonic-clonic electroencephalogram recordings. Medical and Biological Engineering and Computing, 42(4), 516-523.
http://dx.doi.org/10.1007/BF02350993
---------- CHICAGO ----------
Rosso, O.A., Figliola, A., Creso, J., Serrano, E. "Analysis of wavelet-filtered tonic-clonic electroencephalogram recordings" . Medical and Biological Engineering and Computing 42, no. 4 (2004) : 516-523.
http://dx.doi.org/10.1007/BF02350993
---------- MLA ----------
Rosso, O.A., Figliola, A., Creso, J., Serrano, E. "Analysis of wavelet-filtered tonic-clonic electroencephalogram recordings" . Medical and Biological Engineering and Computing, vol. 42, no. 4, 2004, pp. 516-523.
http://dx.doi.org/10.1007/BF02350993
---------- VANCOUVER ----------
Rosso, O.A., Figliola, A., Creso, J., Serrano, E. Analysis of wavelet-filtered tonic-clonic electroencephalogram recordings. Med. Biol. Eng. Comput. 2004;42(4):516-523.
http://dx.doi.org/10.1007/BF02350993