Nonlinear dynamical systems with chaos and big data: A case study of epileptic seizure prediction and control

A Shafique, M Sayeed, K Tsakalis - Guide to big data applications, 2018 - Springer
The modeling of dynamic behavior of systems is a ubiquitous problem in all facets of human
endeavors. Importantly so, dynamical systems have been studied and modeled since the …

Modeling of epilepsy based on chaotic artificial neural network

S Panahi, Z Aram, S Jafari, J Ma, JC Sprott - Chaos, Solitons & Fractals, 2017 - Elsevier
Epilepsy is a long-term chronic neurological disorder that is characterized by seizures. One
type of epilepsy is simple partial seizures that are localized to one area on one side of the …

[PDF][PDF] Design and implementation of neural network based chaotic system model for the dynamical control of brain stimulation

L Zhang - BRAININFO 2017, 2017 - academia.edu
Brain stimulation has been used in practice to treat neurological diseases, such as
Parkinson's Disease and Epilepsy. However, the stimulation signals are generated based …

Artificial neural networks model design of Lorenz chaotic system for EEG pattern recognition and prediction

L Zhang - 2017 IEEE Life Sciences Conference (LSC), 2017 - ieeexplore.ieee.org
This paper presents the preliminary work of a multidisciplinary brain research program. The
goal of this research program is to generate accurate and effective signals for non-invasive …

Development of reconfigurable control schemes for epileptic seizures

S Subbian - 2021 Seventh International conference on Bio …, 2021 - ieeexplore.ieee.org
Advanced research in neuroscience recognized electrical stimulation as a well-accepted
treatment to suppress neurological disorders like Epilepsy, Parkinson's, mental depression …

[PDF][PDF] Analysis of EEG signals using nonlinear dynamics and chaos: a review

G Rodriguez-Bermudez… - Applied mathematics …, 2015 - naturalspublishing.com
Nonlinear dynamics and chaos theory have been used in neurophysiology with the aim to
understand the complex brain activity from electroencephalographic (EEG) signals …

[HTML][HTML] Searching for a paradigm shift in the research on the epilepsies and associated neuropsychiatric comorbidities. From ancient historical knowledge to the …

N Garcia-Cairasco, G Podolsky-Gondim, J Tejada - Epilepsy & Behavior, 2021 - Elsevier
In this review, we will discuss in four scenarios our challenges to offer possible solutions for
the puzzle associated with the epilepsies and neuropsychiatric comorbidities. We need to …

A new chaotic network model for epilepsy

S Panahi, T Shirzadian, M Jalili, S Jafari - Applied Mathematics and …, 2019 - Elsevier
Epilepsy is a prevalent neurological disorder with symptoms characterized by abnormal
discharge in the brain. According to the classification of the International League Against …

[PDF][PDF] Prediction of the epileptic events' epileptic seizures' by neural networks and expert systems

K Tout, N Sinno, M Mikati - International Journal of Biological and Medical …, 2010 - Citeseer
Many studies have focused on the nonlinear analysis of electroencephalography (EEG)
mainly for the characterization of epileptic brain states. It is assumed that at least two states …

Nonlinear time series analysis in epilepsy

H Osterhage, K Lehnertz - International Journal of Bifurcation and …, 2007 - World Scientific
The framework of the theory of nonlinear dynamics provides powerful concepts and
algorithms to study complicated dynamics such as brain electrical activity …