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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 detection of interictal epileptiform discharge (IED) is crucial for the diagnosis of epilepsy, but automated methods often lack interpretability. This study proposes IED-RAG, an explainable multimodal framework for joint IED detection…

Signal Processing · Electrical Eng. & Systems 2026-02-17 Yu Zhu , Jiayang Guo , Jun Jiang , Peipei Gu , Xin Shu , Duo Chen

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

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

Epilepsy is one of the most prevalent brain disorders that disrupts the lives of millions worldwide. For patients with drug-resistant seizures, there exist implantable devices capable of monitoring neural activity, promptly triggering…

Signal Processing · Electrical Eng. & Systems 2023-10-31 Arman Zarei , Bingzhao Zhu , Mahsa Shoaran

Epileptic seizure detection from EEG signals remains challenging due to the high dimensionality and nonlinear, potentially stochastic, dynamics of neural activity. In this work, we investigate whether features derived from topological data…

Machine Learning · Computer Science 2026-04-15 Sunia Tanweer , Narayan Puthanmadam Subramaniyam , Firas A. Khasawneh

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 that affects normal neural activity. These electrical activities can be recorded as signals containing information about the brain known as Electroencephalography (EEG) signals. Analysis of the EEG…

Signal Processing · Electrical Eng. & Systems 2025-07-10 Fatemeh Valipour , Zahra Valipour , Mani Garousi , Ali Khadem

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

Since the manual detection of electrographic seizures in continuous electroencephalogram (EEG) monitoring is very time-consuming and requires a trained expert, attempts to develop automatic seizure detection are diverse and ongoing. Machine…

Signal Processing · Electrical Eng. & Systems 2019-08-02 Poomipat Boonyakitanont , Apiwat Lek-uthai , Krisnachai Chomtho , Jitkomut Songsiri

Epilepsy is typically diagnosed through electroencephalography (EEG) and long-term video-EEG (vEEG) monitoring. The manual analysis of vEEG recordings is time-consuming, necessitating automated tools for seizure detection. Recent…

Image and Video Processing · Electrical Eng. & Systems 2025-10-21 Valerii A. Zuev , Elena G. Salmagambetova , Stepan N. Djakov , Lev V. Utkin

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

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…

Epilepsy is a prevalent neurological disorder marked by sudden, brief episodes of excessive neuronal activity caused by abnormal electrical discharges, which may lead to some mental disorders. Most existing deep learning methods for…

Machine Learning · Computer Science 2025-10-16 Zexin Wang , Lin Shi , Haoyu Wu , Junru Luo , Xiangzeng Kong , Jun Qi

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

Identifying seizure activities in non-stationary electroencephalography (EEG) is a challenging task, since it is time-consuming, burdensome, and dependent on expensive human resources and subject to error and bias. A computerized seizure…

Signal Processing · Electrical Eng. & Systems 2020-04-29 S. Sheykhivand , T. Yousefi Rezaii , Z. Mousavi , A. Delpak , A. Farzamnia

Objective: A clinical decision support tool that automatically interprets EEGs can reduce time to diagnosis and enhance real-time applications such as ICU monitoring. Clinicians have indicated that a sensitivity of 95% with a specificity…

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

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

Electroencephalography (EEG), as the most common tool for epileptic seizure classification, contains useful information about different physiological states of the brain. Seizure related features in EEG signals can be better identified when…

Signal Processing · Electrical Eng. & Systems 2018-05-15 Amirmasoud Ahmadi , Vahid Shalchyan , Mohammad Reza Daliri
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