Analysis of EEG signal for seizure detection based on WPT
A Arı - Electronics Letters, 2020 - Wiley Online Library
Electroencephalogram (EEG) is a diagnostic method that provides information about the
functioning of the brain. EEG can be used to diagnose the abnormally functioning part of the …
functioning of the brain. EEG can be used to diagnose the abnormally functioning part of the …
Epileptic seizure prediction and classification based on statistical features using LSTM fully connected neural network
Epilepsy is the most common neurological disorder by which over 65 million people are
affected across the world. Recent research has shown a very large interest to predict and …
affected across the world. Recent research has shown a very large interest to predict and …
Comparative Study on Epilepsy Prediction Using Modern Techniques
KS Biju - … on Control, Communication and Computing (ICCC), 2023 - ieeexplore.ieee.org
Epilepsy is a persistent, contagious brain condition that affects about 50 million individuals
worldwide. It is characterized by repeated epilepsy, which are short lived bursts of jerking …
worldwide. It is characterized by repeated epilepsy, which are short lived bursts of jerking …
An Efficient Seizure Prediction System using Convolutional Neural Network and Scalogram of the EEG Signals
VJ Thomas, AS Dhas - 2023 7th International Conference on …, 2023 - ieeexplore.ieee.org
Epilepsy is a life-threatening neurological illness that affects millions of people throughout
the world. The most common symptom of epilepsy is seizures. Seizures are characterized by …
the world. The most common symptom of epilepsy is seizures. Seizures are characterized by …
Comparison of Different Machine Learning Algorithms to Classify Epilepsy Seizure from EEG Signals
P Kunekar, C Kumawat, V Lande, S Lokhande… - Engineering …, 2024 - mdpi.com
Recurrent seizures are a symptom of a central nervous system disease called epilepsy. The
duration of these seizures lasts less than a few seconds or sometimes minutes. There are …
duration of these seizures lasts less than a few seconds or sometimes minutes. There are …
[PDF][PDF] Prediction and detection of epileptic seizure by analysing EEG signals
Epilepsy is one of the common neurological disorders characterized by a sudden and
recurrent malfunction of the brain that is termed “seizure”, affecting around 50 million …
recurrent malfunction of the brain that is termed “seizure”, affecting around 50 million …
A review on epileptic seizure detection and prediction using soft computing techniques
Epilepsy is a disorder of the central nervous system in which a considerably large number of
neurons at a certain instance of time show abnormal electrical activity. Worldwide according …
neurons at a certain instance of time show abnormal electrical activity. Worldwide according …
Epilepsy Prediction Using Spark
P Pravalika, S Shabeer, J Meenakshi… - Conference of Innovative …, 2022 - Springer
One of the most frequent neurological disorders in the world is epilepsy. The ability to detect
upcoming seizures early has a significant impact on the lives of epileptic patients. In this …
upcoming seizures early has a significant impact on the lives of epileptic patients. In this …
Expert model for detection of epileptic activity in EEG signature
T Gandhi, BK Panigrahi, M Bhatia, S Anand - Expert Systems with …, 2010 - Elsevier
Seizure detection and classification using signal processing methods has been an important
issue of research for the last two decades. In the present study, a novel scheme was …
issue of research for the last two decades. In the present study, a novel scheme was …
Deep‐learning‐based seizure detection and prediction from electroencephalography signals
FE Ibrahim, HM Emara, W El‐Shafai… - International Journal …, 2022 - Wiley Online Library
Electroencephalography (EEG) is among the main tools used for analyzing and diagnosing
epilepsy. The manual analysis of EEG must be conducted by highly trained clinicians or …
epilepsy. The manual analysis of EEG must be conducted by highly trained clinicians or …