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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…

This paper introduces an innovative approach to Attention-deficit/hyperactivity disorder (ADHD) diagnosis by employing deep learning (DL) techniques on electroencephalography (EEG) signals. This method addresses the limitations of current…

Computers and Society · Computer Science 2024-12-04 Medha Pappula , Syed Muhammad Anwar

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

Epilepsy is one of the common neurological disorders characterized by recurrent and uncontrollable seizures, which seriously affect the life of patients. In many cases, electroencephalograms signal can provide important physiological…

Neurons and Cognition · Quantitative Biology 2023-08-15 Mohammad Reza Yousefi , Saina Golnejad , Melika Mohammad Hosseini , Amin Dehghani

In this paper, we propose a deep learning-based algorithm to improve the performance of automatic speech recognition (ASR) systems for aphasia, apraxia, and dysarthria speech by utilizing electroencephalography (EEG) features recorded…

EEG monitoring has an important milestone provide valuable information of those candidates who suffer from epilepsy.In this paper human normal and epileptic Electroencephalogram signals are analyzed with popular and efficient signal…

Computational Engineering, Finance, and Science · Computer Science 2018-02-26 Debadatta Dash

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

Electroencephalography signals allow to explore the functional activity of the brain cortex in a non-invasive way. However, the analysis of these signals is not straightforward due to the presence of different artifacts and the very low…

Neurons and Cognition · Quantitative Biology 2022-01-24 Nicolás Gallego-Molina , Marco Formoso , Andrés Ortiz , Francisco J. Martínez-Murcia , Juan L. Luque

Diagnosing sleep disorders is an important focus in neuroscience and engineering, as these conditions involve issues such as insufficient sleep, frequent awakenings, and difficulty reaching deep sleep. Accurate detection based on brain…

Neurons and Cognition · Quantitative Biology 2025-09-03 Mohammad Reza Yousefi , Reza Rahimi

Epilepsy is one of the most common and yet diverse set of chronic neurological disorders. This excessive or synchronous neuronal activity is termed seizure. Electroencephalogram signal processing plays a significant role in detection and…

Signal Processing · Electrical Eng. & Systems 2021-09-29 Paul Grant , Md Zahidul Islam

Dyslexia, affecting an estimated 10% to 20% of the global population, significantly impairs learning capabilities, highlighting the need for innovative and accessible diagnostic methods. This paper investigates the effectiveness of…

Machine Learning · Computer Science 2025-06-16 Kevin Cogan , Vuong M. Ngo , Mark Roantree

Epilepsy is a neurological condition such that it affects the brain and the nervous system. It is characterized by recurrent seizures, which are physical reactions to sudden, usually brief, excessive electrical discharges in a group of…

Signal Processing · Electrical Eng. & Systems 2018-07-30 Asmaa Hamad , Aboul Ella Hassanien , Aly A. Fahmy , Essam H. Houssein

Electroencephalogram (EEG) signals are effective tools towards seizure analysis where one of the most important challenges is accurate detection of seizure events and brain regions in which seizure happens or initiates. However, all…

Machine Learning · Computer Science 2023-01-18 Thi Kieu Khanh Ho , Narges Armanfard

Learning disabilities like dysgraphia, dyslexia, dyspraxia, etc. interfere with academic achievements but have also long terms consequences beyond the academic time. It is widely admitted that between 5% to 10% of the world population is…

Other Computer Science · Computer Science 2020-05-14 Gilles Richard , Mathieu Serrurier

Electroencephalography (EEG) during sleep is used by clinicians to evaluate various neurological disorders. In sleep medicine, it is relevant to detect macro-events (> 10s) such as sleep stages, and micro-events (<2s) such as spindles and…

Signal Processing · Electrical Eng. & Systems 2018-07-17 Stanislas Chambon , Valentin Thorey , Pierrick J. Arnal , Emmanuel Mignot , Alexandre Gramfort

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

Electroencephalography (EEG) is a complex signal and can require several years of training to be correctly interpreted. Recently, deep learning (DL) has shown great promise in helping make sense of EEG signals due to its capacity to learn…

Machine Learning · Computer Science 2019-01-23 Yannick Roy , Hubert Banville , Isabela Albuquerque , Alexandre Gramfort , Tiago H. Falk , Jocelyn Faubert

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

Electroencephalogram (EEG) decoding aims to identify the perceptual, semantic, and cognitive content of neural processing based on non-invasively measured brain activity. Traditional EEG decoding methods have achieved moderate success when…

Signal Processing · Electrical Eng. & Systems 2022-03-09 Xun Chen , Chang Li , Aiping Liu , Martin J. McKeown , Ruobing Qian , Z. Jane Wang

Electroencephalogram (EEG) is an important diagnostic test that physicians use to record brain activity and detect seizures by monitoring the signals. There have been several attempts to detect seizures and abnormalities in EEG signals with…

Machine Learning · Computer Science 2022-03-22 Kwanhyung Lee , Hyewon Jeong , Seyun Kim , Donghwa Yang , Hoon-Chul Kang , Edward Choi