On estimating phenomenological model states for epileptic seizure prediction
Clicks: 1
ID: 310045
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
0.0
/100
1 views
0 readers
AI Quality Assessment
Not analyzed
Readership in this journal
Ranked #336 of 490 articles by views in Frontiers in surgery
Most read
Least read
Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 490 in total.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
The prediction of epileptic seizure, like the disease itself, is a very old but largely unresolved problem. The prediction may highly improve the quality of life for an epileptic patient. A low cost measurement like Electroencephalogram (EEG) involves the non-invasive monitoring of the brain voltage signals to detect the epileptic seizure. This work aims at finding ways to estimate the internal states of the neuron population by looking at the measured EEG signals so that the seizure onset may be predicted in advance. If one may estimate the states of the neural population, then by relating to the bifurcation horizon, one may find the seizure onset time. To find such states one need an estimator/observer of a neuronal state space model. Most of the neuronal models, be it biological or phenomenological, are nonlinear. If a linear or any other approximation is used for the observer design, the bifurcation horizon may not be accurate enough. The biological models of neural population have the barrier of determining all the physiological parameters of a patient which may be bit limiting. Phenomenological neuron model like Epileptor is adapted, which is a nonlinear and discontinuous model, estimating its states may help in finding the bifurcation parameters. However, the nonlinearities are of Lipschitz and monotonic class. Using Linear Matrix Inequality solu-tions, a Lipschitz Nonlinear model-based Observer is developed and tested in simulation, without using approximations of any kind. The simulation shows high fidelity of the observer to the model at hand estimating the states helping in determining the bifurcation parameters.
| Reference Key |
imported_1768918443_696f8daba06a5
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Bhatti, Aamer Iqbal |
| Journal | Frontiers in surgery |
| Year | Year not found |
| DOI |
10.3389/fams.2026.1709607
|
| URL | |
| Keywords | Keywords not found |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.