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Autor(en): 
  • Harikumar Rajaguru
  • Ganesh Babu Chidambaram
  • Vigneshkumar Arunachalam
  • EEG Signal Classification Using Hidden Markov Model 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 2 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 7-14 Tagen versandfertig
    Veröffentlichung:  November 2018  
    Genre:  Ratgeber 
    ISBN:  9786139961320 
    EAN-Code: 
    9786139961320 
    Verlag:  LAP Lambert Academic Publishing 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 220 mm / B 150 mm / D 4 mm 
    Gewicht:  107 gr 
    Seiten:  60 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    This book emphasize on Epilepsy which is a neurological disorder with preponderance of about 1-2% of the world's population. It is due to excessive synchronization of cortical neuronal networks and is characterized by sudden recurrent and transient disturbances of perception or behavior. Epileptic seizures are classified as partial or focal, generalized, unilateral and unclassified seizures. Focal epileptic seizures involve only part of cerebral hemisphere and in corresponding parts of the body. Generalized epileptic seizures involve the entire brain and produce bilateral motor symptoms usually with loss of consciousness. Both types of epileptic seizures can occur at all ages.One of the most important tools for diagnosing Epilepsy includes monitoring brain activity through the electroencephalogram (EEG). The EEG signature is transient waveform of isolated spikes, spike trains.It also assists in classifying the underlying epileptic syndrome. The feature extraction is done by Independent Component Analysis (ICA) and final risk level classification is done by Hidden Markov Model (HMM). Performance evaluation is done by Kappa function and Mean Square Error (MSE).

      



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