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Related papers: Classifying seizure generation mechanisms: A criti…

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Classification of seizure type is a key step in the clinical process for evaluating an individual who presents with seizures. It determines the course of clinical diagnosis and treatment, and its impact stretches beyond the clinical domain…

Signal Processing · Electrical Eng. & Systems 2024-03-06 David Ahmedt-Aristizabal , Tharindu Fernando , Simon Denman , Lars Petersson , Matthew J. Aburn , Clinton Fookes

In this chapter we review phenomenological models of seizure like activity. We discuss dynamical mechanisms for seizure onset and offset, preictal spikes, spike and wave complexes and status epilepticus, highlighting the role played by the…

Neurons and Cognition · Quantitative Biology 2020-07-07 Maria Luisa Saggio , Viktor Jirsa

Epileptic seizure detection and classification in clinical electroencephalogram data still is a challenge, and only low sensitivity with a high rate of false positives has been achieved with commercially available seizure detection tools,…

Signal Processing · Electrical Eng. & Systems 2020-07-14 Tomas Iesmantas , Robertas Alzbutas

Seizure type identification is essential for the treatment and management of epileptic patients. However, it is a difficult process known to be time consuming and labor intensive. Automated diagnosis systems, with the advancement of machine…

Signal Processing · Electrical Eng. & Systems 2023-03-09 Hezam Albaqami , Ghulam Mubashar Hassan , Amitava Datta

Epilepsy is a common neurological disorder characterized by abrupt seizures. Although seizures may appear random, they are often preceded by early warning signs in neural signals, notably, critical slowing down, a phenomenon in which the…

Systems and Control · Electrical Eng. & Systems 2024-11-12 Yuzhen Qin , Marcel van Gerven

Accurate classification of seizure types plays a crucial role in the treatment and disease management of epileptic patients. Epileptic seizure types not only impact the choice of drugs but also the range of activities a patient can safely…

Machine Learning · Computer Science 2020-08-13 Subhrajit Roy , Umar Asif , Jianbin Tang , Stefan Harrer

Epilepsy is one of the most common brain diseases that affect more than 1\% of the world's population. It is characterized by recurrent seizures, which come in different types and are treated differently. Electroencephalography (EEG) is…

Signal Processing · Electrical Eng. & Systems 2022-06-09 Hezam Albaqami , Ghulam Mubashar Hassan , Amitava Datta

Reliable seizure detection is critical for diagnosing and managing epilepsy, yet clinical workflows remain dependent on time-consuming manual EEG interpretation. While machine learning has shown promise, existing approaches often rely on…

Machine Learning · Computer Science 2025-08-12 Bartlomiej Chybowski , Shima Abdullateef , Hollan Haule , Alfredo Gonzalez-Sulser , Javier Escudero

Electroencephalogram, an influential equipment for analyzing humans activities and recognition of seizure attacks can play a crucial role in designing accurate systems which can distinguish ictal seizures from regular brain alertness, since…

Signal Processing · Electrical Eng. & Systems 2018-06-26 Amirmasoud Ahmadi , Mahsa Behroozi , Vahid Shalchyan , Mohammad Reza Daliri

Epilepsy is a neurological brain disorder which life threatening and gives rise to recurrent seizures that are unprovoked. It occurs due to the abnormal chemical changes in our brain. Over the course of many years, studies have been…

Signal Processing · Electrical Eng. & Systems 2022-10-13 Muhammad Shoaib Farooq , Aimen Zulfiqar , Shamyla Riaz

Objective: Epileptic seizures are relatively common in critically-ill children admitted to the pediatric intensive care unit (PICU) and thus serve as an important target for identification and treatment. Most of these seizures have no…

Epileptic seizures are characterized by abnormal and excessive neural activity, where cortical network dynamics seem to become unstable. However, most of the time, during seizure-free periods, cortex of epilepsy patients shows perfectly…

Neurons and Cognition · Quantitative Biology 2021-04-06 Annika Hagemann , Jens Wilting , Bita Samimizad , Florian Mormann , Viola Priesemann

Epileptic seizures are one of the most well-known dysfunctions of the nervous system. During a seizure, a highly synchronized behavior of neural activity is observed that can cause symptoms ranging from mild sensual malfunctions to the…

Neurons and Cognition · Quantitative Biology 2011-08-01 Christian Kuehn , Christian Meisel

An epileptic seizure is a transient event of abnormal excessive neuronal discharge in the brain. This unwanted event can be obstructed by detection of electrical changes in the brain that happen before the seizure takes place. The automatic…

Machine Learning · Computer Science 2016-04-29 Z. Roshan Zamir

Deep learning models have recently shown great success in classifying epileptic patients using EEG recordings. Unfortunately, classification-based methods lack a sound mechanism to detect the onset of seizure events. In this work, we…

Machine Learning · Computer Science 2025-03-04 Zheng Chen , Yasuko Matsubara , Yasushi Sakurai , Jimeng Sun

To define the neural networks responsible of the epileptic seizure, we had to study the electrophysiological signal in a proper way. The early recognition of the seizure build up could also be defined through the time space mapping of the…

Signal Processing · Electrical Eng. & Systems 2019-11-19 Ridha Jarray , Nawel Jmail , Abir Hadriche , Tarek Frikha , Chokri Ben Amar

Identifying epileptic seizures through analysis of the electroencephalography (EEG) signal becomes a standard method for the diagnosis of epilepsy. Manual seizure identification on EEG by trained neurologists is time-consuming,…

Machine Learning · Computer Science 2019-06-07 X. Yao , X. Li , Q. Ye , Y. Huang , Q. Cheng , G. -Q. Zhang

Epilepsy is one of the most common neurological diseases, characterized by transient and unprovoked events called epileptic seizures. Electroencephalogram (EEG) is an auxiliary method used to perform both the diagnosis and the monitoring of…

Automatic classification of epileptic seizure types in electroencephalograms (EEGs) data can enable more precise diagnosis and efficient management of the disease. This task is challenging due to factors such as low signal-to-noise ratios,…

Machine Learning · Computer Science 2020-10-01 Umar Asif , Subhrajit Roy , Jianbin Tang , Stefan Harrer

Epilepsy is the most common neurological disorder and an accurate forecast of seizures would help to overcome the patient's uncertainty and helplessness. In this contribution, we present and discuss a novel methodology for the…

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