An environment for complex behaviour detection in bio-potential experiments

  • Received: 01 October 2007 Accepted: 29 June 2018 Published: 01 March 2008
  • MSC : 92C55.

  • 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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  • 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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