The seizure prediction problem in epilepsy: Cellular nonlinear networks
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
Abstract
70 million people are affected by epilepsy which is the most common chronic neurological disorder worldwide. About 70% of patients can expect an effective seizure control with medication. The realization of an implantable device capable of detecting impending seizures, warning patients and rendering some kind of treatment would be of great benefit. In this contribution, a brief history of epilepsy and an introduction to terminology and symptoms are given followed by a short summary of current research going on in the field of seizure prediction. Afterwards, an introduction to Cellular Nonlinear Networks (CNN , a paradigm for high speed computation) is given and finally a presentation of 4 different CNN based approaches to epileptic seizure prediction will convey a vision of the methods possibly used one day on an implantable seizure warning device.
Details
Original language | English |
---|---|
Pages (from-to) | 8-20 |
Number of pages | 13 |
Journal | IEEE circuits and systems magazine |
Volume | 12 |
Issue number | 4 |
Publication status | Published - 29 Nov 2012 |
Peer-reviewed | Yes |
External IDs
ORCID | /0000-0001-7436-0103/work/142240337 |
---|