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In this study, we present a criterion based on the analysis of EEG signals through the mean of the conventional power spectral density (PSD) in the aim to localize and detect the epileptic area of the brain. Firstly, as the EEG signals are…

Applications · Statistics 2016-10-31 Mahamat Ali Issaka , Ali S. Dabye , Lamine Gueye

Electroencephalography (EEG) is essential for the diagnosis of epilepsy, but it requires expertise and experience to identify abnormalities. It is thus crucial to develop automated models for the detection of abnormalities in EEGs related…

Signal Processing · Electrical Eng. & Systems 2021-11-23 Taku Shoji , Noboru Yoshida , Toshihisa Tanaka

Understanding the complex interplay between the brain and a dynamic environment necessitates the continuous generation and updating of expectations for forthcoming events and their corresponding sensory and motor responses. This study…

Adaptation and Self-Organizing Systems · Physics 2023-08-24 Sina Khoonbani , Hasan Ramezanian

Epilepsy is one of the common neurological disorders characterized by recurrent and uncontrollable seizures, which seriously affect the life of patients. In many cases, electroencephalograms signal can provide important physiological…

Neurons and Cognition · Quantitative Biology 2023-08-15 Mohammad Reza Yousefi , Saina Golnejad , Melika Mohammad Hosseini , Amin Dehghani

One of epileptology's fundamental aims is the formulation of a universal, internally consistent seizure definition. To assess this aim's feasibility, three signal analysis methods were applied to a seizure time series and performance…

Neurons and Cognition · Quantitative Biology 2011-11-15 Ivan Osorio , Alexey Lyubushin , Didier Sornette

Epilepsy is one of the most serious neurological diseases, affecting 1-2% of the world's population. The diagnosis of epilepsy depends heavily on the recognition of epileptic waves, i.e., disordered electrical brainwave activity in the…

Signal Processing · Electrical Eng. & Systems 2023-06-26 Junru Chen , Yang Yang , Tao Yu , Yingying Fan , Xiaolong Mo , Carl Yang

Epilepsy is a prevalent neurological disorder characterized by recurrent and unpredictable seizures, necessitating accurate prediction for effective management and patient care. Application of machine learning (ML) on electroencephalogram…

Signal Processing · Electrical Eng. & Systems 2023-08-11 Md. Simul Hasan Talukder , Rejwan Bin Sulaiman

Seizure onset detection in electroencephalography (EEG) signals is a challenging task due to the non-stereotyped seizure activities as well as their stochastic and non-stationary characteristics in nature. Joint spectral-temporal features…

Signal Processing · Electrical Eng. & Systems 2022-02-15 Xucun Yan , Dongping Yang , Zihuai Lin , Branka Vucetic

The experimental proofs of strong time invariance violation in optics are discussed. Time noninvariance is the only real physical base for explanation the origin of the most phenomena in nonlinear optics. The experimental study of forward…

General Physics · Physics 2007-05-23 V. A. Kuz'menko

Electroencephalography (EEG) provides a way to understand, and evaluate neurotransmission. In this context, time-locked EEG activity or event-related potentials (ERPs) are often used to capture neural activity related to specific mental…

Signal Processing · Electrical Eng. & Systems 2024-11-21 Mario Molina , Lorenzo J. Tardon , Ana M. Barbancho , Irene De-Torres , Isabel Barbancho

Epilepsy is a neurological disorder and for its detection, encephalography (EEG) is a commonly used clinical approach. Manual inspection of EEG brain signals is a time-consuming and laborious process, which puts heavy burden on neurologists…

Computer Vision and Pattern Recognition · Computer Science 2018-01-17 Ihsan Ullah , Muhammad Hussain , Emad-ul-Haq Qazi , Hatim Aboalsamh

Quantifying irreversibility of a system using finite information constitutes a major challenge in stochastic thermodynamics. We introduce an observable that measures the time-reversal asymmetry between two states after a given time lag. Our…

Statistical Mechanics · Physics 2023-12-18 Shiling Liang , Simone Pigolotti

Purpose: The understanding of brain activity, and in particular events such as epileptic seizures, lies on the characterisation of the dynamics of the neural networks. The theory of non-linear dynamics provides signal analysis techniques…

Medical Physics · Physics 2007-05-23 C. Silva , I. R. Pimentel , A. Andrade , J. P. Foreid , E. Ducla-Soares

Current pain assessment within hospitals often relies on self-reporting or non-specific EKG vital signs. This system leaves critically ill, sedated, and cognitively impaired patients vulnerable to undertreated pain and opioid overuse.…

Machine Learning · Computer Science 2025-10-08 Aavid Mathrawala , Dhruv Kurup , Josie Lau

Time reversal of vast classes of phenomena has direct implications with predictability, causality and the second principle of thermodynamics. We analyze in detail time reversibility of a paradigmatic dissipative nonlinear dynamical system,…

Chaotic Dynamics · Physics 2023-06-26 Constantino Tsallis , Ernesto P. Borges

The relation between time series irreversibility and entropy production has been recently investigated in thermodynamic systems operating away from equilibrium. In this work we explore this concept in the context of financial time series.…

Statistical Finance · Quantitative Finance 2016-01-11 Lucas Lacasa , Ryan Flanagan

Quantifying the complex/multifractal organization of the brain signals is crucial to fully understanding the brain processes and structure. In this contribution, we performed the multifractal analysis of the electroencephalographic (EEG)…

Intracranial EEG (iEEG) is the gold standard technique for epileptogenic zone (EZ) localisation, but requires a hypothesis of which tissue is epileptogenic, guided by qualitative analysis of seizure semiology and other imaging modalities…

Active matter encompasses systems whose individual consituents dissipate energy to exert propelling forces on their environment. This rapidly developing field harbors a dynamical phenomenology with no counterpart in passive systems. The…

Statistical Mechanics · Physics 2023-12-19 Jérémy O'Byrne , Yariv Kafri , Julien Tailleur , Frédéric van Wijland

One notable method for recording brainwaves to identify neurological problems is electroencephalography (hereafter EEG). A trained neuro physician can learn more about how the brain functions through the use of EEGs. However conventionally,…

Neurons and Cognition · Quantitative Biology 2024-02-26 Hari Prasad SV