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    A new dissimilarity index of EEG signals for epileptic seizure detection

    , Article Final Program and Abstract Book - 4th International Symposium on Communications, Control, and Signal Processing, ISCCSP 2010, 3 March 2010 through 5 March 2010 ; March , 2010 ; 9781424462858 (ISBN) Niknazar, M ; Mousavi, S. R ; Vosoughi Vahdat, B ; Shamsollahi, M. B ; Sayyah, M ; Sharif University of Technology
    2010
    Abstract
    Epileptic seizures are generated by an abnormal synchronization of neurons. Since epileptic seizures are unforeseeable for the patients, epileptic seizures detection is an interesting issue in epileptology, that novel approaches to understand the mechanism of epileptic seizures. In this study we analyzed invasive electroencephalogram (EEG) recordings in patients suffering from medically intractable focal epilepsy with a nonlinear method called, dissimilarity index. In order to detect epileptic seizures Bhattacharyya distance between trajectory matrix of reference window during an interval quite distant in time from any seizure and trajectory matrix of present window is employed to measure... 

    Application of Bhattacharyya distance as a dissimilarity index for automated prediction of epileptic seizures in rats

    , Article 2010 International Conference on Intelligent and Advanced Systems, ICIAS 2010, 15 June 2010 through 17 June 2010 ; 2010 ; 9781424466238 (ISBN) Niknazar, M ; Vosoughi Vahdat, B ; Shamsollahi, M. B ; Sayyah, M ; Sharif University of Technology
    Abstract
    Seizures are defined as manifest of excessive and hypersynchronous activity of neurons in the cerebral cortex and represent a frequent malfunction of the human central nervous system. Therefore, the search for precursors and predictors of a seizure is of utmost clinical relevance and may even guide us to a deep understanding of the seizure generating mechanisms. In this study we analyzed invasive electroencephalogram (EEG) recordings in rats with experimentally induced generalized epilepsy with a nonlinear method called, dissimilarity index. In order to predict epileptic seizures automatically, Bhattacharyya distance between trajectory matrix of reference window, during an interval quite... 

    Recursive spectral analysis of natural time series based on eigenvector matrix perturbation for online applications

    , Article IET Signal Processing ; Volume 5, Issue 6 , 2011 , Pages 515-526 ; 17519675 (ISSN) Mirmomeni, M ; Lucas, C ; Araabi, B. N ; Moshiri, B ; Bidar, M. R ; Sharif University of Technology
    2011
    Abstract
    Singular spectrum analysis (SSA) is a well-studied approach in signal processing. SSA has originally been designed to extract information from short noisy chaotic time series and to enhance the signal-to-noise ratio. SSA is good for offline applications; however, many applications, such as modelling, analysis, and prediction of time-varying and non-stationary time series, demand for online analysis. This study introduces a recursive algorithm called recursive SSA as a modification to regular SSA for dynamic and online applications. The proposed method is based on eigenvector matrix perturbation approach. After recursively calculating the covariance matrix of the trajectory matrix, R-SSA...