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Carte Seizure Detection Using A Support Vector Machine Algorithm Kevin Freedman

Seizure Detection Using A Support Vector Machine Algorithm

A Novel Multi-Measurement Approach

Autor: Kevin Freedman
Limbă: engleză
Legare: Carte broșată
Editura: LAP Lambert Academic Publishing
Disponibilitate: În depozitul extern
Expediem în 5-8 zile
235.46 lei
Epilepsy is the second most common neurologic disorder which is characterized by recurrent and spont...

Informații despre carte

Autor
Kevin Freedman
Limbă
engleză
Legare
Carte - Carte broșată
Publicat
2009
Pagini
76
EAN
9783838324296
Enbook ID
06938206
Editura
LAP Lambert Academic Publishing
Greutate
131
Dimensiuni
150 x 220 x 5

Descriere completă

Epilepsy is the second most common neurologic disorder which is characterized by recurrent and spontaneous seizures. Seizures occur unpredictably which makes everyday tasks such as driving and working extremely difficult resulting in a reduced quality of life. Epilepsy monitoring units measure the electrical activity of the brain using electroencephalography in an attempt to locate the epileptic brain tissue. However since seizures occur unpredictably and are generally infrequent, long recording times generate massive quantities of data. Automating this process using a seizure detection algorithm will ultimately save time and money, allow for superior and safer care of patients, and provide a better diagnostic tool. Although seizure detection has been well studied in the laboratory and clinic, a widely accepted algorithm has not been developed largely due to the fact that automated routines do not perform as well as a neurologist. In order to improve performance, we tested the hypothesis that multiple algorithms would work better than any single approach. Multiple algorithms were used as feature extractors and were implemented into a support vector machine (SVM) algorithm.

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