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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

A Magnetoencephalography (MEG) time-series recording consists of multi-channel signals collected by superconducting sensors, with each signal's intensity reflecting magnetic field changes over time at the sensor location. Automating…

Signal Processing · Electrical Eng. & Systems 2025-01-22 Hanyang Dong , Shurong Sheng , Xiongfei Wang , Jiahong Gao , Yi Sun , Wanli Yang , Kuntao Xiao , Pengfei Teng , Guoming Luan , Zhao Lv

Magnetoencephalography (MEG) recordings of patients with epilepsy exhibit spikes, a typical biomarker of the pathology. Detecting those spikes allows accurate localization of brain regions triggering seizures. Spike detection is often…

Computer Vision and Pattern Recognition · Computer Science 2023-10-16 Pauline Mouches , Thibaut Dejean , Julien Jung , Romain Bouet , Carole Lartizien , Romain Quentin

Approximately over 50 million people worldwide suffer from epilepsy. Traditional diagnosis of epilepsy relies on tedious visual screening by highly trained clinicians from lengthy EEG recording that contains the presence of seizure (ictal)…

Artificial Intelligence · Computer Science 2009-04-27 Forrest Sheng Bao , Jue-Ming Gao , Jing Hu , Donald Y. -C. Lie , Yuanlin Zhang , K. J. Oommen

Magnetoencephalography (MEG) allows the non-invasive detection of interictal epileptiform discharges (IEDs). Clinical MEG analysis in epileptic patients traditionally relies on the visual identification of IEDs, which is time consuming and…

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

Epilepsy is a neurological disorder classified as the second most serious neurological disease known to humanity, after stroke. Localization of the epileptogenic zone is an important step for epileptic patient treatment, which starts with…

Epilepsy affects around 50 million people globally. Electroencephalography (EEG) or Magnetoencephalography (MEG) based spike detection plays a crucial role in diagnosis and treatment. Manual spike identification is time-consuming and…

Machine Learning · Statistics 2026-03-16 Fangyi Wei , Jiajie Mo , Kai Zhang , Haipeng Shen , Srikantan Nagarajan , Fei Jiang

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

The presence of interictal epileptiform discharges (IEDs) in electroencephalogram (EEG) recordings is a critical biomarker of epilepsy. Even trained neurologists find detecting IEDs difficult, leading many practitioners to turn to machine…

Epilepsy and psychogenic non-epileptic seizures often present with similar seizure-like manifestations but require fundamentally different management strategies. Misdiagnosis is common and can lead to prolonged diagnostic delays,…

Computation and Language · Computer Science 2026-03-31 Shuang Zhou , Kai Yu , Zaifu Zhan , Huixue Zhou , Min Zeng , Feng Xie , Zhiyi Sha , Rui Zhang

Epilepsy is a highly prevalent brain condition with many serious complications arising from it. The majority of patients which present to a clinic and undergo electroencephalogram (EEG) monitoring would be unlikely to experience seizures…

Signal Processing · Electrical Eng. & Systems 2023-12-14 Matthew McDougall , Hezam Albaqami , Ghulam Mubashar Hassan , Amitava Datta

The analysis of interictal epileptiform discharges (IEDs) in magnetoencephalography (MEG) or electroencephalogram (EEG) recordings represents a critical component in the diagnosis of epilepsy. However, manual analysis of these IEDs, which…

Computer Vision and Pattern Recognition · Computer Science 2025-08-28 Kuntao Xiao , Xiongfei Wang , Pengfei Teng , Yi Sun , Yong Zhang , Wanli Yang , Zikang Xu , Liang Zhang , Hanyang Dong , Guoming Luan , Shurong Sheng

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

Early warning for epilepsy patients is crucial for their safety and well-being, in particular to prevent or minimize the severity of seizures. Through the patients' EEG data, we propose a meta learning framework to improve the prediction of…

Machine Learning · Computer Science 2024-01-12 Peng Zhang , Ting Gao , Jin Guo , Jinqiao Duan , Sergey Nikolenko

Epilepsy is one of the most common neurological disorders, affecting about 1% of the population at all ages. Detecting the development of epilepsy, i.e., epileptogenesis (EPG), before any seizures occur could allow for early interventions…

Machine Learning · Computer Science 2020-06-18 Diyuan Lu , Sebastian Bauer , Valentin Neubert , Lara Sophie Costard , Felix Rosenow , Jochen Triesch

Epilepsy is a network disease. The epileptic network usually involves spatially distributed brain regions. In this context, noninvasive M/EEG source connectivity is an emerging technique to identify functional brain networks at cortical…

Neurons and Cognition · Quantitative Biology 2016-08-18 Mahmoud Hassan , Isabelle Merlet , Ahmad Mheich , Aya Kabbara , Arnaud Biraben , Anca Nica , Fabrice Wendling

Magnetoencephalography (MEG) is a cutting-edge neuroimaging technique that measures the intricate brain dynamics underlying cognitive processes with an unparalleled combination of high temporal and spatial precision. MEG data analytics has…

Neurons and Cognition · Quantitative Biology 2025-05-20 Arthur Dehgan , Hamza Abdelhedi , Vanessa Hadid , Irina Rish , Karim Jerbi

Epilepsy, affecting approximately 50 million people globally, is characterized by abnormal brain activity and remains challenging to treat. The diagnosis of epilepsy relies heavily on electroencephalogram (EEG) data, where specialists…

Interictal spikes and sharp waves in human EEG are characteristic signatures of epilepsy. These potentials originate as a result of synchronous, pathological discharge of many neurons. The reliable detection of such potentials has been the…

Biological Physics · Physics 2009-11-10 Miroslaw Latka , Ziemowit Was , Andrzej Kozik , Bruce J. West
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