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Objective: Epilepsy is a chronic neurological disorder characterized by the occurrence of spontaneous seizures, which affects about one percent of the world's population. Most of the current seizure detection approaches strongly rely on…

Signal Processing · Electrical Eng. & Systems 2020-02-04 Xiang Zhang , Lina Yao , Manqing Dong , Zhe Liu , Yu Zhang , Yong Li

Epilepsy or the occurrence of epileptic seizures, is one of the world's most well-known neurological disorders affecting millions of people. Seizures mostly occur due to non-coordinated electrical discharges in the human brain and may cause…

Machine Learning · Computer Science 2023-03-14 Hitesh Raju , Ankit Sharma , Aoife Smeaton , Alan F. Smeaton

While Deep Learning (DL) is often considered the state-of-the art for Artificial Intelligence-based medical decision support, it remains sparsely implemented in clinical practice and poorly trusted by clinicians due to insufficient…

Machine Learning · Computer Science 2020-12-23 Valentin Gabeff , Tomas Teijeiro , Marina Zapater , Leila Cammoun , Sylvain Rheims , Philippe Ryvlin , David Atienza

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

Implantable, closed-loop devices for automated early detection and stimulation of epileptic seizures are promising treatment options for patients with severe epilepsy that cannot be treated with traditional means. Most approaches for early…

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

Parkinson's disease is a widespread neurodegenerative condition necessitating early diagnosis for effective intervention. This paper introduces an innovative method for diagnosing Parkinson's disease through the analysis of human EEG…

Signal Processing · Electrical Eng. & Systems 2024-05-03 Maryam Allahbakhshi , Aylar Sadri , Seyed Omid Shahdi

Epilepsy is a prevalent neurological disorder affecting 50 million individuals worldwide and 1.2 million Americans. There exist millions of pediatric patients with intractable epilepsy, a condition in which seizures fail to come under…

Machine Learning · Computer Science 2023-09-07 Bliss Singhal , Fnu Pooja

Magnetoencephalography (MEG) is an advanced imaging technique used to measure the magnetic fields outside the human head produced by the electrical activity inside the brain. Various source localization methods in MEG require the knowledge…

Methodology · Statistics 2017-07-06 Zhigang Yao , Ye Zhang , Zhidong Bai , William F. Eddy

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

Epilepsy is one of the most common neurological disorders. This disease requires reliable and efficient seizure detection methods. Electroencephalography (EEG) is the gold standard for seizure monitoring, but its manual analysis is a…

Signal Processing · Electrical Eng. & Systems 2025-12-17 Annika Stiehl , Nicolas Weeger , Christian Uhl , Dominic Bechtold , Nicole Ille , Stefan Geißelsöder

In this work, we present a neuromorphic system that combines for the first time a neural recording headstage with a signal-to-spike conversion circuit and a multi-core spiking neural network (SNN) architecture on the same die for recording,…

Signal Processing · Electrical Eng. & Systems 2021-06-09 Mohammadali Sharifshazileh , Karla Burelo , Johannes Sarnthein , Giacomo Indiveri

Early management and better clinical outcomes for epileptic patients depend on seizure prediction. The accuracy and false alarm rates of existing systems are often compromised by their dependence on static thresholds and basic…

Signal Processing · Electrical Eng. & Systems 2025-01-29 Mathan Kumar Mounagurusamy , Thiyagarajan V S , Abdur Rahman , Shravan Chandak , D. Balaji , Venkateswara Rao Jallepalli

Epilepsy is a prevalent neurological disorder that affects millions of individuals globally, and continuous monitoring coupled with automated seizure detection appears as a necessity for effective patient treatment. To enable long-term care…

Objective: Post-traumatic epilepsy (PTE) is a debilitating neurological disorder that develops after traumatic brain injury (TBI). Early prediction of PTE remains challenging due to heterogeneous clinical data, limited positive cases, and…

Machine Learning · Computer Science 2026-04-17 Wenhui Cui , Nicholas Swingle , Anand A. Joshi , Dileep Nair , Richard M. Leahy

Objective: The aim of this study is to develop an efficient and reliable epileptic seizure prediction system using intracranial EEG (iEEG) data, especially for people with drug-resistant epilepsy. The prediction procedure should yield…

Neural and Evolutionary Computing · Computer Science 2019-04-09 Ramy Hussein , Mohamed Osama Ahmed , Rabab Ward , Z. Jane Wang , Levin Kuhlmann , Yi Guo

[$^{18}$F]fluorodeoxyglucose (FDG) positron emission tomography (PET) has emerged as a crucial tool in identifying the epileptic focus, especially in cases where magnetic resonance imaging (MRI) diagnosis yields indeterminate results. FDG…

Computer Vision and Pattern Recognition · Computer Science 2024-02-05 Wentao Chen , Jiwei Li , Xichen Xu , Hui Huang , Siyu Yuan , Miao Zhang , Tianming Xu , Jie Luo , Weimin Zhou

EEG is a non-invasive technique for recording brain bioelectric activity, which has potential applications in various fields such as human-computer interaction and neuroscience. However, there are many difficulties in analyzing EEG data,…

Signal Processing · Electrical Eng. & Systems 2018-01-18 Yumeng Ye , Haichun Liu , TianHong Zhang , Changchun Pan , Genke Yang , JiJun Wang , Robert C. Qiu

Post-traumatic epilepsy (PTE) is a life-long complication of traumatic brain injury (TBI) and is a major public health problem that has an estimated incidence that ranges from 2%-50%, depending on the severity of the TBI. Currently, the…

Quantitative Methods · Quantitative Biology 2020-11-17 Md Navid Akbar , Marianna La Rocca , Rachael Garner , Dominique Duncan , Deniz Erdoğmuş

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