EEG Signal Analysis and Classification

Techniques and Applications

Häftad, Engelska, 2018

Av Siuly Siuly, Yan Li, Yanchun Zhang

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This book presents advanced methodologies in two areas related to electroencephalogram (EEG) signals: detection of epileptic seizures and identification of mental states in brain computer interface (BCI) systems.

Produktinformation

Utgivningsdatum2018-07-25
Mått155 x 235 x 15 mm
Vikt417 g
FormatHäftad
SpråkEngelska
SerieHealth Information Science
Antal sidor256
FörlagSpringer International Publishing AG
ISBN9783319837918

Tillhör följande kategorier

Tillämpad datateknik inom Data och it
Systemvetenskap och AI inom Data och it
Biomedicinsk teknik inom Medicin
Elektronik och kommunikationer inom Naturvetenskap och teknik
Artificiell intelligens inom Data och it

Electroencephalogram (EEG) and its background.- Significance of EEG signals in medical and health research.- Objectives and structures of the book.- Random sampling in the detection of epileptic EEG signals.- A novel clustering technique for the detection of epileptic seizures.- A statistical framework for classifying epileptic seizure from multi-category EEG signals.- Injecting principal component analysis with the OA scheme in the epileptic EEG signal classification.- Cross-correlation aided logistic regression model for the identification of motor imagery EEG signals in BCI applications.- Modified CC-LR Algorithm for identification of MI based EEG signals.- Improving prospective performance in the MI recognition: LS-SVM with tuning hyper parameters.- Comparative study: Motor area EEG and All-channels EEG.- Optimum allocation aided Naive Bayes based learning process for the detection of MI tasks.- Summary discussions on the methods, future directions and conclusions.