An environment for complex behaviour detection in bio-potential experiments
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Dipartimento di Ingegneria Elettrica, Elettronica e dei Sistemi, Universita degli Studi di Catania, Viale A. Doria 6, 95125 Catania
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Dipartimento di Ingegneria Elettrica Elettronica e dei Sistemi, Facoltà di Ingegneria, Università degli Studi di Catania, viale A. Doria 6, 95125 Catania
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Received:
01 October 2007
Accepted:
29 June 2018
Published:
01 March 2008
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MSC :
92C55.
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We propose BioS (Bio-potential Study) as a new virtual data anal-
ysis and management environment.It was devised to cope with the physiological
signals, in order to manage different data using advanced methods of analy-
sis and to find a simple way to decode and interpret data. BioS has been
structured as a flexible, modular, and portable environment. It includes sev-
eral modules as data importing and loading, data visualization (1D, 2D, 3D),
pre-processing (frequency and saturation filtering, statistical analysis), spatio-
temporal processing such as power spectrum, independent component analysis
(ICA) in spatial and time domain, and nonlinear analysis for the extraction
of the maximum Lyapunov exponent and d ∞(d-inifnite) using optimized al-
gorithms. The environment provides a user-friendly Graphic User Interface
that allows inexperienced users to perform complex analyses and to speed up
experimental data processing.
Citation: Maide Bucolo, Federica Di Grazia, Luigi Fortuna, Mattia Frasca, Francesca Sapuppo. An environment for complex behaviour detection in bio-potential experiments[J]. Mathematical Biosciences and Engineering, 2008, 5(2): 261-276. doi: 10.3934/mbe.2008.5.261
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Abstract
We propose BioS (Bio-potential Study) as a new virtual data anal-
ysis and management environment.It was devised to cope with the physiological
signals, in order to manage different data using advanced methods of analy-
sis and to find a simple way to decode and interpret data. BioS has been
structured as a flexible, modular, and portable environment. It includes sev-
eral modules as data importing and loading, data visualization (1D, 2D, 3D),
pre-processing (frequency and saturation filtering, statistical analysis), spatio-
temporal processing such as power spectrum, independent component analysis
(ICA) in spatial and time domain, and nonlinear analysis for the extraction
of the maximum Lyapunov exponent and d ∞(d-inifnite) using optimized al-
gorithms. The environment provides a user-friendly Graphic User Interface
that allows inexperienced users to perform complex analyses and to speed up
experimental data processing.
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