Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/84951
Title: Analysis and Classification of Eeg Signals for Detection of Epileptic Seizures
Researcher: Sood, Meenakshi
Guide(s): Bhooshan, Sunil Vidya
Keywords: Computer Aided Diagnostic Systems
Electroencephalogram
Epilepsy
Sensitivity
Specificity
University: Jaypee University of Information Technology, Solan
Completed Date: 2015
Abstract: Epilepsy is a persistent constantly recurring neurological brain disorder characterized by abnormal electrical activity in the brain. Epilepsy is not only a disorder but rather acts as a syndrome with divergent symptoms involving spasmodic abnormal electrical activities in the brain. Clinical data relevant to such abnormalities is complex context dependent and multidimensional and such data generates an amalgamation of computing research challenges. Electroencephalogram EEG is one of the most clinically and a scientifically utilized signal recorded from human brain and is powerful source of providing valuable insight of the brain dynamics. Accurate and careful analyses of these signals play a prominent role in diagnosis of brain diseases and many cognitive processes. newlineEEG technique has excellent temporal resolution noninvasiveness usability and low setup costs while capturing brain signals which makes it popular in this arena of research. The electroencephalogram recordings of epileptic subjects are visually inspected and analyzed by trained neurologists or radiologists for clinical diagnosis of epileptic seizures and possible treatment plans. However due to the complex time consuming high dimensional nature of the EEG event recordings visual inspections of EEG signals often result in errors. Therefore there is a need to develop automatic systems for classifying the recorded EEG signals. newline
URI: http://hdl.handle.net/10603/84951
Appears in Departments:Department of Electronics and Communication Engineering

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1_title.pdf132.91 kBAdobe PDFView/Open
2_certificate.pdf450.35 kBAdobe PDFView/Open
3_declaration.pdf103.25 kBAdobe PDFView/Open
4_acknowledgement.pdf16.54 kBAdobe PDFView/Open
5_table of contents.pdf25.49 kBAdobe PDFView/Open
6_list of figures.pdf68.33 kBAdobe PDFView/Open
7_abstract.pdf13.49 kBAdobe PDFView/Open
8_chapter 1.pdf1.42 MBAdobe PDFView/Open
9_chapter 2.pdf66.56 kBAdobe PDFView/Open


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