Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/530685
Title: | Efficient Detection Of Epileptic Seizure Based On Artificial Neural Network |
Researcher: | Kavya B S |
Guide(s): | S N Prasad |
Keywords: | Engineering Engineering and Technology Engineering Electrical and Electronic |
University: | REVA University |
Completed Date: | 2023 |
Abstract: | As per the worldwide data Epileptic Seizures are very well know and common newlinebrain disorder from all the possible brain disorders available worldwide. However, newlinethese epileptic seizures can be identified using varied signal processing methods. newlineEpilepsy can be defined as a neurological disorder in which frequent seizures occurs. newlineThese seizures demonstrate excessive, extreme and hyperactive neurological newlineconditions inside brain. According to several reports, there are 1% of total world newlinepopulation actively suffering from epilepsy disorder and 3-5% people of world newlinepopulation suffers from epileptic seizure at least once in their lifetime. However, newlineelliptic seizures and other brain disorders are efficiently identified from newlineElectroencephalogram (EEG) signals because of the advancement and development newlinein computer aided technologies. Here, EEG signals are employed to examine and newlineanalyse brain activities of human. These EEG signals are vastly utilized in medical newlineapplications for brain disorder diagnosis. Moreover, Electroencephalogram (EEG) can newlinebe defined as the key diagnostic method for identifying seizures. Monitoring of newlinenumerous hours or days is required in EEG diagnostic method for examining epileptic newlineseizures. Thus, this method is quite complicated, tedious and time-consuming. This newlineprocess becomes even more complicated when subjects consists of intra cerebral newlineelectrodes and EEG signal contains multiple channels or more than 100 channels. newlineGenerally, seizures are restricted to fewer channels and single electrode. Thus, newlineevaluation of exact channel in EEG is important while detecting elliptic seizures. So, newlinean automatic seizure detection technique can make process faster and make seizure newline |
Pagination: | |
URI: | http://hdl.handle.net/10603/530685 |
Appears in Departments: | School of Electronics & Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 93.92 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 865.11 kB | Adobe PDF | View/Open | |
03_content.pdf | 162.41 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 146.11 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 752.08 kB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 493.97 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 1.52 MB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 547.59 kB | Adobe PDF | View/Open | |
09_annexures.pdf | 427.64 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 1.32 MB | Adobe PDF | View/Open |
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