English
Related papers

Related papers: Detecting Epileptic Seizures from EEG Data using N…

200 papers

One notable method for recording brainwaves to identify neurological problems is electroencephalography (hereafter EEG). A trained neuro physician can learn more about how the brain functions through the use of EEGs. However conventionally,…

Neurons and Cognition · Quantitative Biology 2024-02-26 Hari Prasad SV

Accurate classification of seizure types plays a crucial role in the treatment and disease management of epileptic patients. Epileptic seizure types not only impact the choice of drugs but also the range of activities a patient can safely…

Machine Learning · Computer Science 2020-08-13 Subhrajit Roy , Umar Asif , Jianbin Tang , Stefan Harrer

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

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

The diagnosis of epilepsy generally includes a visual inspection of EEG recorded data by the Neurologist, with the purpose of checking the occurrence of transient waveforms called interictal epileptiform discharges. These waveforms have…

Computer Vision and Pattern Recognition · Computer Science 2016-06-08 Andre Rosado , Agostinho C Rosa

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…

Seizures are one of the defining symptoms in patients with epilepsy, and due to their unannounced occurrence, they can pose a severe risk for the individual that suffers it. New research efforts are showing a promising future for the…

Machine Learning · Computer Science 2021-08-09 Carlos H. Mendoza-Cardenas , Austin J. Brockmeier

Neonates are highly susceptible to seizures, often leading to short or long-term neurological impairments. However, clinical manifestations of neonatal seizures are subtle and often lead to misdiagnoses. This increases the risk of…

Refractory epileptic patients can suffer a seizure at any moment. Seizure prediction would substantially improve their lives. In this work, based on scalp EEG and its transformation into images, the likelihood of an epileptic seizure…

Signal Processing · Electrical Eng. & Systems 2022-04-15 Tiago Leal , Fabio Lopes , Cesar Teixeira , Antonio Dourado

Background: Neonatal seizures are a neurological emergency that require urgent treatment. They are hard to diagnose clinically and can go undetected if EEG monitoring is unavailable. EEG interpretation requires specialised expertise which…

Machine Learning · Computer Science 2024-05-17 Robert Hogan , Sean R. Mathieson , Aurel Luca , Soraia Ventura , Sean Griffin , Geraldine B. Boylan , John M. O'Toole

This demo presents SeizNet, an innovative system for predicting epileptic seizures benefiting from a multi-modal sensor network and utilizing Deep Learning (DL) techniques. Epilepsy affects approximately 65 million people worldwide, many of…

Epilepsy is one of the most common neurological disorders that can be diagnosed through electroencephalogram (EEG), in which the following epileptic events can be observed: pre-ictal, ictal, post-ictal, and interictal. In this paper, we…

Machine Learning · Computer Science 2021-02-12 Jefferson Tales Oliva , João Luís Garcia Rosa

Repeated epileptic seizures impair around 65 million people worldwide and a successful prediction of seizures could significantly help patients suffering from refractory epilepsy. For two dogs with yearlong intracranial…

Neurons and Cognition · Quantitative Biology 2022-01-13 Hongliu Yang , Matthias Eberlein , Jens Müller , Ronald Tetzlaff

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

In this work we study how to apply topological data analysis to create a method suitable to classify EEGs of patients affected by epilepsy. The topological space constructed from the collection of EEGs signals is analyzed by Persistent…

Neurons and Cognition · Quantitative Biology 2020-09-14 Marco Piangerelli , Matteo Rucco , Emanuela Merelli

Epilepsy and psychogenic non-epileptic seizures often present with similar seizure-like manifestations but require fundamentally different management strategies. Misdiagnosis is common and can lead to prolonged diagnostic delays,…

Computation and Language · Computer Science 2026-03-31 Shuang Zhou , Kai Yu , Zaifu Zhan , Huixue Zhou , Min Zeng , Feng Xie , Zhiyi Sha , Rui Zhang

The electroencephalographic (EEG) data intracerebrally recorded from 20 epileptic humans with different brain origins of focal epilepsies or types of seizures, ages and sexes are investigated (nearly 700 million data). Multi channel…

Biological Physics · Physics 2010-02-19 Caglar Tuncay

Seizure type identification is essential for the treatment and management of epileptic patients. However, it is a difficult process known to be time consuming and labor intensive. Automated diagnosis systems, with the advancement of machine…

Signal Processing · Electrical Eng. & Systems 2023-03-09 Hezam Albaqami , Ghulam Mubashar Hassan , Amitava Datta

We present the implementation of seizure detection algorithms based on a minimal number of EEG channels on a parallel ultra-low-power embedded platform. The analyses are based on the CHB-MIT dataset, and include explorations of different…

Information transmission in the human brain is a fundamentally dynamic network process. In partial epilepsy, this process is perturbed and highly synchronous seizures originate in a local network, the so-called epileptogenic zone (EZ),…

Neurons and Cognition · Quantitative Biology 2019-06-19 Simona Olmi , Spase Petkoski , Maxime Guye , Fabrice Bartolomei , Viktor Jirsa
‹ Prev 1 4 5 6 7 8 10 Next ›