Seizure Detection Using A Support Vector Machine Algorithm: A Novel Multi-Measurement Approach - Brossura

Freedman, Kevin

Brossura

ISBN 10: 3838324293 ISBN 13: 9783838324296

Casa editrice: LAP Lambert Academic Publishing, 2009

Riassunto

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.

Dettagli dell'edizione

• Editore: LAP Lambert Academic Publishing
• Data di pubblicazione: 2009
• Lingua: Inglese
• ISBN 10: 3838324293
• ISBN 13: 9783838324296
• Rilegatura: Copertina flessibile
• Numero di pagine: 76
• Contatto del produttore: non disponibile
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