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Epilepsy is a neurological disorder arising from anomalies of the electrical activity in the brain, affecting about 0.5--0.8\% of the world population. Several studies investigated the relationship between seizures and brainwave…

Machine Learning · Computer Science 2018-01-25 Paolo Detti , Garazi Zabalo Manrique de Lara , Renato Bruni , Marco Pranzo , Francesco Sarnari

Localizing the seizure onset zone (SOZ) as a step of presurgical planning leads to higher efficiency in surgical and stimulation treatments. However, the clinical localization including structural, ictal, and invasive data acquisition and…

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

Epilepsy is one of the most prevalent neurological conditions, where an epileptic seizure is a transient occurrence due to abnormal, excessive and synchronous activity in the brain. Electroencephalogram signals emanating from the brain may…

Neurons and Cognition · Quantitative Biology 2023-12-05 Paul Grant , Md Zahidul Islam

Epilepsy is one of the most common and yet diverse set of chronic neurological disorders. This excessive or synchronous neuronal activity is termed seizure. Electroencephalogram signal processing plays a significant role in detection and…

Signal Processing · Electrical Eng. & Systems 2021-09-29 Paul Grant , Md Zahidul Islam

Intracranial EEG (IEEG) is used for 2 main purposes, to determine: (1) if epileptic networks are amenable to focal treatment and (2) where to intervene. Currently these questions are answered qualitatively and sometimes differently across…

Predicting post-operative seizure freedom using functional correlation networks derived from interictal intracranial EEG has shown some success. However, there are important challenges to consider. 1: electrodes physically closer to each…

By computerized analysis of cortical activity recorded via fMRI for pediatric epilepsy patients, we implement algorithmic localization of epileptic seizure focus within one of eight cortical lobes. Our innovative machine learning techniques…

Quantitative Methods · Quantitative Biology 2018-12-12 Rasoul Hekmati , Robert Azencott , Wei Zhang , Zili D. Chu , Michael J. Paldino

The use of EEG signal to diagnose several brain abnormalities is well-established in the literature. Particularly, epileptic seizure can be detected using EEG signals and several works were done in this field. The joint time-frequency…

Signal Processing · Electrical Eng. & Systems 2020-01-24 Abdullah Othman , Mohamed A. Deriche

An ability to map seizure-generating brain tissue, i.e., the seizure onset zone (SOZ), without recording actual seizures could reduce the duration of invasive EEG monitoring for patients with drug-resistant epilepsy. A widely-adopted…

Real time seizure detection is a fundamental problem in computational neuroscience towards diagnosis and treatment's improvement of epileptic disease. We propose a real-time computational method for tracking and detection of epileptic…

Quantitative Methods · Quantitative Biology 2024-06-17 Ximena Fernández , Diego Mateos

The underlying dynamics for the electroencephalographic (EEG) recordings from humans but especially epilepsy patients are usually not completely known. However, the ictal activity is claimed to be characterized by synchronous oscillations…

Biological Physics · Physics 2010-08-09 Caglar Tuncay

Epilepsy is a well-known neuronal disorder that can be identified by interpretation of the electroencephalogram (EEG) signal. Usually, the length of an EEG signal is quite long which is challenging to interpret manually. In this work, we…

Machine Learning · Computer Science 2019-03-07 Md Mursalin , Syed Shamsul Islam , Md Kislu Noman , Adel Ali Al-Jumaily

The two-point central difference is a common algorithm in biological signal processing and is particularly useful in analyzing physiological signals. In this paper, we develop a model-based classification method to detect epileptic seizures…

Applications · Statistics 2020-06-01 Antonio Quintero-Rincon , Carlos D'Giano , Hadj Batatia

Recent advances in material technology and in micro- and nano-electronics have profoundly changed the design of intracranial electrophysiology electrodes. It is now possible to manufacture electrodes that record cortical activity at a…

Neurons and Cognition · Quantitative Biology 2024-02-06 Pierre Bourdillon , Linnea Evanson

The diagnosis of epilepsy generally includes a visual inspection of EEG recorded data by the Neurologist, with the purpose of checking the occurrence of transient waveforms called interictal epileptiform discharges. These waveforms have…

Computer Vision and Pattern Recognition · Computer Science 2016-06-08 Andre Rosado , Agostinho C Rosa

Epileptic biomarkers play a crucial role in identifying the origin of seizures, an essential aspect of pre-surgical planning for epilepsy treatment. These biomarkers can vary significantly over time. By studying these temporal fluctuations,…

Signal Processing · Electrical Eng. & Systems 2025-11-11 Mehdi Zekriyapanah Gashti , Mostafa Mohammadpour , Hassan Eshkiki , Vahid Ghanbarizadeh

There is increasing evidence for specific cortical and subcortical large-scale human epileptic networks to be involved in the generation, spread, and termination of not only primary generalized but also focal onset seizures. The complex…

Neurons and Cognition · Quantitative Biology 2016-10-07 Christian Geier , Marie-Therese Kuhnert , Christian E. Elger , Klaus Lehnertz

Recognition of epileptic focal point is the important diagnosis when screening the epilepsy patients for latent surgical cures. The accurate localization is challenging one because of the low spatial resolution images with more noisy data.…

Computer Vision and Pattern Recognition · Computer Science 2013-03-05 A. Meena , R. Raja

Epilepsy is one of the most common neurological disorders that greatly impair patient' daily lives. Traditional epileptic diagnosis relies on tedious visual screening by neurologists from lengthy EEG recording that requires the presence of…

Artificial Intelligence · Computer Science 2016-11-18 Forrest Sheng Bao , Donald Yu-Chun Lie , Yuanlin Zhang
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