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Cited by 363

The DOI matches its Crossref record; 131 of the 131 references it cites were found in a registry or an index.

Epileptic seizure prediction and control

Iasemidis, L.D.·2003·IEEE Transactions on Biomedical Engineering
DOI 10.1109/tbme.2003.810705
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Abstract

Epileptic seizures are manifestations of epilepsy, a serious brain dynamical disorder second only to strokes. Of the world's approximately 50 million people with epilepsy, fully 1/3 have seizures that are not controlled by anti-convulsant medication. The field of seizure prediction, in which engineering technologies are used to decode brain signals and search for precursors of impending epileptic seizures, holds great promise to elucidate the dynamical mechanisms underlying the disorder, as well as to enable implantable devices to intervene in time to treat epilepsy. There is currently an explosion of interest in this field in academic centers and medical industry with clinical trials underway to test potential prediction and intervention methodology and devices for Food and Drug Administration (FDA) approval. This invited paper presents an overview of the application of signal processing methodologies based upon the theory of nonlinear dynamics to the problem of seizure prediction. Broader application of these developments to a variety of systems requiring monitoring, forecasting and control is a natural outgrowth of this field.

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Metadata

Authors
Iasemidis, L. D.
Venue
IEEE Transactions on Biomedical Engineering
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2003-05
Volume
50
Issue
5
Pages
549-558
ISSN
0018-9294 (ISSN-L)
DOI
10.1109/tbme.2003.810705
OpenAlex
W2159398070
Cited by
363
References
131
FWCI
6.47
Type
journal article
Language
en
Open access
closed

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