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Related papers: Demo: Multi-Modal Seizure Prediction System

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Electroencephalogram (EEG) is a prominent way to measure the brain activity for studying epilepsy, thereby helping in predicting seizures. Seizure prediction is an active research area with many deep learning based approaches dominating the…

Signal Processing · Electrical Eng. & Systems 2020-11-19 Zaid Bin Tariq , Arun Iyengar , Lara Marcuse , Hui Su , Bülent Yener

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

An accurate seizure prediction system enables early warnings before seizure onset of epileptic patients. It is extremely important for drug-refractory patients. Conventional seizure prediction works usually rely on features extracted from…

Signal Processing · Electrical Eng. & Systems 2021-08-18 Yankun Xu , Jie Yang , Shiqi Zhao , Hemmings Wu , Mohamad Sawan

Epilepsy is a chronic, noncommunicable brain disorder, and sudden seizure onsets can significantly impact patients' quality of life and health. However, wearable seizure-predicting devices are still limited, partly due to the bulky size of…

Signal Processing · Electrical Eng. & Systems 2025-07-22 Ruifeng Zheng , Cong Chen , Shuang Wang , Yiming Liu , Lin You , Jindong Lu , Ruizhe Zhu , Guodao Zhang , Kejie Huang

Epilepsy which is characterized by seizures is studied using EEG signals by recording the electrical activity of the brain. Different types of communication between different parts of the brain are characterized by many state of the art…

Machine Learning · Computer Science 2020-09-29 Mohammad Mansour , Fouad Khnaisser , Hmayag Partamian

Epilepsy significantly impacts global health, affecting about 65 million people worldwide, along with various animal species. The diagnostic processes of epilepsy are often hindered by the transient and unpredictable nature of seizures.…

Signal Processing · Electrical Eng. & Systems 2026-04-21 Z. Wang , S. Li , Dongrui Wu

With the advancement in artificial intelligence (AI) and machine learning (ML) techniques, researchers are striving towards employing these techniques for advancing clinical practice. One of the key objectives in healthcare is the early…

Machine Learning · Computer Science 2020-02-06 Khansa Rasheed , Adnan Qayyum , Junaid Qadir , Shobi Sivathamboo , Patrick Kwan , Levin Kuhlmann , Terence O'Brien , Adeel Razi

Epilepsy is one of the most occurring neurological disease globally emerged back in 4000 BC. It is affecting around 50 million people of all ages these days. The trait of this disease is recurrent seizures. In the past few decades, the…

Machine Learning · Computer Science 2021-11-08 Virender Ranga , Shivam Gupta , Jyoti Meena , Priyansh Agrawal

Epilepsy is a disorder of the brain denoted by frequent seizures. The symptoms of seizure include confusion, abnormal staring, and rapid, sudden, and uncontrollable hand movements. Epileptic seizure detection methods involve neurological…

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

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

Epilepsy is the second most common brain disorder after migraine. Automatic detection of epileptic seizures can considerably improve the patients' quality of life. Current Electroencephalogram (EEG)-based seizure detection systems encounter…

Signal Processing · Electrical Eng. & Systems 2018-03-28 Ramy Hussein , Hamid Palangi , Rabab Ward , Z. Jane Wang

Epilepsy is common neurological diseases, affecting about 0.6-0.8 % of world population. Epileptic patients suffer from chronic unprovoked seizures, which can result in broad spectrum of debilitating medical and social consequences. Since…

Quantitative Methods · Quantitative Biology 2017-06-13 Sachin S. Talathi

Approximately, 50 million people in the world are affected by epilepsy. For patients, the anti-epileptic drugs are not always useful and these drugs may have undesired side effects on a patient's health. If the seizure is predicted the…

Machine Learning · Computer Science 2019-12-16 Hazrat Ali , Feroz Karim , Junaid Javed Qureshi , Adnan Omer Abuassba , Mohammad Farhad Bulbul

A variety of screening approaches have been proposed to diagnose epileptic seizures, using electroencephalography (EEG) and magnetic resonance imaging (MRI) modalities. Artificial intelligence encompasses a variety of areas, and one of its…

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 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…

Epilepsy is a chronic neurological disorder affecting 1\% of people worldwide, deep learning (DL) algorithms-based electroencephalograph (EEG) analysis provides the possibility for accurate epileptic seizure (ES) prediction, thereby…

Signal Processing · Electrical Eng. & Systems 2022-05-10 Yankun Xu , Jie Yang , Mohamad Sawan

Seizure forecasting may provide patients with timely warnings to adapt their daily activities and help clinicians deliver more objective, personalized treatments. While recent work has convincingly demonstrated that seizure risk assessment…

Neurons and Cognition · Quantitative Biology 2019-06-10 Christian Meisel , Rima El Atrache , Michele Jackson , Sarah Schubach , Claire Ufongene , Tobias Loddenkemper

Epileptic seizures cause abnormal brain activity, and their unpredictability can lead to accidents, underscoring the need for long-term seizure prediction. Although seizures can be predicted by analyzing electroencephalogram (EEG) signals,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-03 Guorui Lu , Jing Peng , Bingyuan Huang , Chang Gao , Todor Stefanov , Yong Hao , Qinyu Chen