Abstract
The collection and interpretation of electroencephalogram (EEG) signals are laborious and time-consuming activities, requiring a trained specialist to perform them. Automatic detection of epilepsy may be a solution. However, research on the subject has focused on detecting specific, non-generalized epilepsies in a larger patient population. Decomposition of signals, through singular spectrum analysis, of records of patients with epilepsy for subsequent verification of the energy limit. These records were available in a publicly accessible signal bank. The use of different weights to calculate means and standard deviations of the energy series and different sample sizes contributed to improve the diagnosis.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.