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Epileptic seizures are considered as abnormally hypersynchronous neuronal activities of the brain. Do hypersynchronous neuronal activities in a brain region lead to seizure or the hypersynchronous activities take place due to the…

Neurons and Cognition · Quantitative Biology 2013-01-08 Kaushik Majumdar , Pradeep D. Prasad , Shailesh Verma

Epilepsy is a brain disorder due to abnormalactivity of neurons and recording of seizures is of primary interest in the evaluation of epileptic patients. A seizureis the phenomenon of rhythmicity discharge from either a local area or the…

Signal Processing · Electrical Eng. & Systems 2019-03-26 Hesam Akbari , Somayeh Saraf Esmaili , Sima Farzollah Zadeh

Epilepsy is a chronic neurological disorder affecting more than 65 million people worldwide and manifested by recurrent unprovoked seizures. The unpredictability of seizures not only degrades the quality of life of the patients, but it can…

Signal Processing · Electrical Eng. & Systems 2019-11-13 Damian Pascual , Amir Aminifar , David Atienza , Philippe Ryvlin , Roger Wattenhofer

Background: Epilepsy is a neurological illness affecting the brain that makes people more likely to experience frequent, spontaneous seizures. There has to be an accurate automated method for measuring seizure frequency and severity in…

Signal Processing · Electrical Eng. & Systems 2023-05-09 Salim Rukhsar , Anil K. Tiwari

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

Electroencephalogram (EEG) monitoring and objective seizure identification is an essential clinical investigation for some patients with epilepsy. Accurate annotation is done through a time-consuming process by EEG specialists.…

Medical Physics · Physics 2021-04-22 Yikai Yang , Nhan Duy Truong , Christina Maher , Armin Nikpour , Omid Kavehei

Epilepsy affects 50 million people worldwide and is one of the most common serious neurological disorders. Seizure detection and classification is a valuable tool for diagnosing and maintaining the condition. An automated classification…

Signal Processing · Electrical Eng. & Systems 2022-08-22 Scot Davidson , Niamh McCallan , Kok Yew Ng , Pardis Biglarbeigi , Dewar Finlay , Boon Leong Lan , James McLaughlin

Epileptic seizure prediction from electroencephalographic (EEG) recordings remains challenging due to strong inter-patient variability and the complex temporal structure of neural signals. This paper presents a patient-adaptive transformer…

Machine Learning · Computer Science 2026-03-31 Mohamed Mahdi , Asma Baghdadi

Information transmission in the human brain is a fundamentally dynamic network process. In partial epilepsy, this process is perturbed and highly synchronous seizures originate in a local network, the so-called epileptogenic zone (EZ),…

Neurons and Cognition · Quantitative Biology 2019-06-19 Simona Olmi , Spase Petkoski , Maxime Guye , Fabrice Bartolomei , Viktor Jirsa

Over the past decade, high-frequency oscillations (HFOs) have been studied as a promising biomarker for localizing epileptogenic areas in drug-resistant patients requiring pre-surgical intervention, while exploiting intracranial…

Signal Processing · Electrical Eng. & Systems 2024-12-24 Zayneb Sadek , Abir Hadriche , Rahma Maalej , Nawel Jmail

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…

Epilepsy is one of the most common neurological disorders affecting up to 1% of the world's population and approximately 2.5 million people in the United States. Seizures in more than 30% of epilepsy patients are refractory to…

Signal Processing · Electrical Eng. & Systems 2019-08-23 Md Abu Sayeed , Saraju P. Mohanty , Elias Kougianos

Electrophysiological observation plays a major role in epilepsy evaluation. However, human interpretation of brain signals is subjective and prone to misdiagnosis. Automating this process, especially seizure detection relying on scalp-based…

Machine Learning · Computer Science 2018-07-06 David Ahmedt-Aristizabal , Clinton Fookes , Kien Nguyen , Sridha Sridharan

Automated epileptic seizure detection from electroencephalogram (EEG) remains challenging due to significant individual differences in EEG patterns across patients. While existing studies achieve high accuracy with patient-specific…

Signal Processing · Electrical Eng. & Systems 2025-05-22 Rina Tazaki , Tomoyuki Akiyama , Akira Furui

Machine learning (ML)-based analysis of electroencephalograms (EEGs) is playing an important role in advancing neurological care. However, the difficulties in automatically extracting useful metadata from clinical records hinder the…

Computation and Language · Computer Science 2021-09-14 Samarth Rawal , Yogatheesan Varatharajah

Recent studies have shown that seizures can spread and terminate across brain areas via a rich diversity of spatiotemporal patterns. In particular, while the location of the seizure onset area is usually in-variant across seizures in a same…

Neurons and Cognition · Quantitative Biology 2018-05-09 Timothée Proix , Viktor K. Jirsa , Fabrice Bartolomei , Maxime Guye , Wilson Truccolo

The prediction of epileptic seizure has always been extremely challenging in medical domain. However, as the development of computer technology, the application of machine learning introduced new ideas for seizure forecasting. Applying…

Machine Learning · Computer Science 2019-10-08 Haotian Liu , Lin Xi , Ying Zhao , Zhixiang Li

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

In drug-resistant epilepsy, presurgical evaluation of epilepsy can be considered. Magnetoencephalography (MEG) has been shown to be an effective exam to inform the localization of the epileptogenic zone through the localization of…

Computer Vision and Pattern Recognition · Computer Science 2025-10-27 Pauline Mouches , Julien Jung , Armand Demasson , Agnès Guinard , Romain Bouet , Rosalie Marchal , Romain Quentin

Epileptic seizures are one of the most crucial neurological disorders, and their early diagnosis will help the clinicians to provide accurate treatment for the patients. The electroencephalogram (EEG) signals are widely used for epileptic…