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The two-point central difference is a common algorithm in biological signal processing and is particularly useful in analyzing physiological signals. In this paper, we develop a model-based classification method to detect epileptic seizures…

Applications · Statistics 2020-06-01 Antonio Quintero-Rincon , Carlos D'Giano , Hadj Batatia

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

Electroencephalogram, an influential equipment for analyzing humans activities and recognition of seizure attacks can play a crucial role in designing accurate systems which can distinguish ictal seizures from regular brain alertness, since…

Signal Processing · Electrical Eng. & Systems 2018-06-26 Amirmasoud Ahmadi , Mahsa Behroozi , Vahid Shalchyan , Mohammad Reza Daliri

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…

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

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

Automatic classification of epileptic seizure types in electroencephalograms (EEGs) data can enable more precise diagnosis and efficient management of the disease. This task is challenging due to factors such as low signal-to-noise ratios,…

Machine Learning · Computer Science 2020-10-01 Umar Asif , Subhrajit Roy , Jianbin Tang , Stefan Harrer

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

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

Over the past few decades, electroencephalography (EEG) monitoring has become a pivotal tool for diagnosing neurological disorders, particularly for detecting seizures. Epilepsy, one of the most prevalent neurological diseases worldwide,…

Machine Learning · Computer Science 2025-08-08 Andrea Pollastro , Francesco Isgrò , Roberto Prevete

Epilepsy is a neurological disorder arising from anomalies of the electrical activity in the brain, affecting about 0.5--0.8\% of the world population. Several studies investigated the relationship between seizures and brainwave…

Machine Learning · Computer Science 2018-01-25 Paolo Detti , Garazi Zabalo Manrique de Lara , Renato Bruni , Marco Pranzo , Francesco Sarnari

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…

This paper demonstrates the predictive superiority of discrete wavelet transform (DWT) over previously used methods of feature extraction in the diagnosis of epileptic seizures from EEG data. Classification accuracy, specificity, and…

Computational Engineering, Finance, and Science · Computer Science 2021-02-03 Cyrille Feudjio , Victoire Djimna Noyum , Younous Perieukeu Mofendjou , Rockefeller , Ernest Fokoué

Epilepsy affects 50 million people worldwide and is one of the most common serious neurological disorders. Seizure detection and classification is a valuable tool for diagnosing and maintaining the condition. An automated classification…

Signal Processing · Electrical Eng. & Systems 2022-08-22 Scot Davidson , Niamh McCallan , Kok Yew Ng , Pardis Biglarbeigi , Dewar Finlay , Boon Leong Lan , James McLaughlin

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

Epileptic seizures are one of the most crucial neurological disorders, and their early diagnosis will help the clinicians to provide accurate treatment for the patients. The electroencephalogram (EEG) signals are widely used for epileptic…

Epilepsy is one of the most common neurological disorders, typically observed via seizure episodes. Epileptic seizures are commonly monitored through electroencephalogram (EEG) recordings due to their routine and low expense collection. The…

Signal Processing · Electrical Eng. & Systems 2023-01-10 İlkay Yıldız Potter , George Zerveas , Carsten Eickhoff , Dominique Duncan

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…

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

Pattern classification in electroencephalography (EEG) signals is an important problem in biomedical engineering since it enables the detection of brain activity, particularly the early detection of epileptic seizures. In this paper, we…

Applications · Statistics 2024-07-04 Antonio Quintero-Rincón , Jorge Prendes , Valeria Muro , Carlos D'Giano