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The time series captured by a single scalp electrode (plus the reference electrode) of refractory epileptic patients is used to forecast seizures susceptibility. The time series is preprocessed, segmented, and each segment transformed into…

Machine Learning · Computer Science 2022-06-30 Tiago Leal , Antonio Dourado , Fabio Lopes , Cesar Teixeira

Epileptic seizure forecasting, combined with the delivery of preventative therapies, holds the potential to greatly improve the quality of life for epilepsy patients and their caregivers. Forecasting seizures could prevent some potentially…

Signal Processing · Electrical Eng. & Systems 2020-05-18 Nhan Duy Truong , Yikai Yang , Christina Maher , Armin Nikpour , Omid Kavehei

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

Epileptic seizure prediction has gained considerable interest in the computational Epilepsy research community. This paper presents a Machine Learning based method for epileptic seizure prediction which outperforms state-of-the art methods.…

Medical Physics · Physics 2021-06-09 Remy Ben Messaoud , Mario Chavez

An epileptic seizure is a transient event of abnormal excessive neuronal discharge in the brain. This unwanted event can be obstructed by detection of electrical changes in the brain that happen before the seizure takes place. The automatic…

Machine Learning · Computer Science 2016-04-29 Z. Roshan Zamir

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 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…

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

Epileptic seizures are neurological disorders characterized by abnormal and excessive electrical activity in the brain, resulting in recurrent seizure events. Electroencephalogram (EEG) signals are widely used for seizure diagnosis due to…

Machine Learning · Computer Science 2026-04-02 Ferdaus Anam Jibon , Fazlul Hasan Siddiqui , F. Deeba , Gahangir Hossain

To predict an epileptic event means the ability to determine in advance the time of the seizure with the highest possible accuracy. A correct prediction benchmark for epilepsy events in clinical applications is a typical problem in…

Applications · Statistics 2020-06-03 Antonio Quintero-Rincon , Carlos D'Giano , Marcelo Risk

The electroencephalogram (EEG) is one of the most precious technologies to understand the happenings inside our brain and further understand our body's happenings. Automatic prediction of oncoming seizures using the EEG signals helps the…

Signal Processing · Electrical Eng. & Systems 2022-11-08 Abhijeet Bhattacharya

Epilepsy is a disorder of the nervous system that can affect people of any age group. With roughly 50 million people worldwide diagnosed with the disorder, it is one of the most common neurological disorders. The EEG is an indispensable…

Populations and Evolution · Quantitative Biology 2022-02-21 Niamh McCallan , Scot Davidson , Kok Yew Ng , Pardis Biglarbeigi , Dewar Finlay , Boon Leong Lan , James McLaughlin

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

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 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…

Although recent studies have proposed seizure detection algorithms with good sensitivity performance, there is a remained challenge that they were hard to achieve significantly short detection latency in real-time scenarios. In this…

Signal Processing · Electrical Eng. & Systems 2023-06-29 Yankun Xu , Jie Yang , Wenjie Ming , Shuang Wang , Mohamad Sawan

Epilepsy affects more than 50 million people worldwide, making it one of the world's most prevalent neurological diseases. The main symptom of epilepsy is seizures, which occur abruptly and can cause serious injury or death. The ability to…

Signal Processing · Electrical Eng. & Systems 2024-02-06 Zakary Georgis-Yap , Milos R. Popovic , Shehroz S. Khan

Epilepsy is a neurological brain disorder which life threatening and gives rise to recurrent seizures that are unprovoked. It occurs due to the abnormal chemical changes in our brain. Over the course of many years, studies have been…

Signal Processing · Electrical Eng. & Systems 2022-10-13 Muhammad Shoaib Farooq , Aimen Zulfiqar , Shamyla Riaz

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

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
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