Epileptic Seizure Detection in Long-Term EEG Recordings by Using Wavelet-Based Directed Transfer Function

2018 ◽  
Vol 65 (11) ◽  
pp. 2591-2599 ◽  
Author(s):  
Dong Wang ◽  
Doutian Ren ◽  
Kuo Li ◽  
Yiming Feng ◽  
Dan Ma ◽  
...  
Keyword(s):  
Transfer Function ◽  
Epileptic Seizure ◽  
Seizure Detection ◽  
Directed Transfer Function ◽  
Epileptic Seizure Detection ◽  
Eeg Recordings

scholarly journals An Efficient Method for Epileptic Seizure Detection in Long-Term EEG Recordings

2014 ◽  
Vol 07 (12) ◽  
pp. 963-972 ◽  
Author(s):  
Alaa Eldeen Mahmoud Helal ◽  
Ahmed Farag Seddik ◽  
Mohammed Ali Eldosoky ◽  
Ayat Allah Farouk Hussein
Keyword(s):  
Efficient Method ◽  
Epileptic Seizure ◽  
Seizure Detection ◽  
Epileptic Seizure Detection ◽  
Eeg Recordings

Epileptic seizure detection based on improved wavelet neural networks in long-term intracranial EEG

2016 ◽  
Vol 36 (2) ◽  
pp. 375-384 ◽  
Author(s):  
Dongyun Geng ◽  
Weidong Zhou ◽  
Yanli Zhang ◽  
Shujuan Geng
Keyword(s):  
Neural Networks ◽  
Epileptic Seizure ◽  
Seizure Detection ◽  
Wavelet Neural Networks ◽  
Intracranial Eeg ◽  
Epileptic Seizure Detection

Epileptic Seizure Detection with Log-Euclidean Gaussian Kernel-Based Sparse Representation

2016 ◽  
Vol 26 (03) ◽  
pp. 1650011 ◽  
Author(s):  
Shasha Yuan ◽  
Weidong Zhou ◽  
Qi Wu ◽  
Yanli Zhang
Keyword(s):  
Riemannian Manifold ◽  
Sparse Representation ◽  
Epileptic Seizure ◽  
Reproducing Kernel ◽  
Reproducing Kernel Hilbert Space ◽  
Seizure Detection ◽  
Detection Methods ◽  
Gaussian Kernel ◽  
Epileptic Seizure Detection ◽  
Eeg Recordings

Epileptic seizure detection plays an important role in the diagnosis of epilepsy and reducing the massive workload of reviewing electroencephalography (EEG) recordings. In this work, a novel algorithm is developed to detect seizures employing log-Euclidean Gaussian kernel-based sparse representation (SR) in long-term EEG recordings. Unlike the traditional SR for vector data in Euclidean space, the log-Euclidean Gaussian kernel-based SR framework is proposed for seizure detection in the space of the symmetric positive definite (SPD) matrices, which form a Riemannian manifold. Since the Riemannian manifold is nonlinear, the log-Euclidean Gaussian kernel function is applied to embed it into a reproducing kernel Hilbert space (RKHS) for performing SR. The EEG signals of all channels are divided into epochs and the SPD matrices representing EEG epochs are generated by covariance descriptors. Then, the testing samples are sparsely coded over the dictionary composed by training samples utilizing log-Euclidean Gaussian kernel-based SR. The classification of testing samples is achieved by computing the minimal reconstructed residuals. The proposed method is evaluated on the Freiburg EEG dataset of 21 patients and shows its notable performance on both epoch-based and event-based assessments. Moreover, this method handles multiple channels of EEG recordings synchronously which is more speedy and efficient than traditional seizure detection methods.

Automated Real-Time Epileptic Seizure Detection in Scalp EEG Recordings Using an Algorithm Based on Wavelet Packet Transform

2010 ◽  
Vol 57 (7) ◽  
pp. 1639-1651 ◽  
Author(s):  
Ali Shahidi Zandi ◽  
Manouchehr Javidan ◽  
Guy A Dumont ◽  
Reza Tafreshi
Keyword(s):  
Real Time ◽  
Epileptic Seizure ◽  
Wavelet Packet ◽  
Seizure Detection ◽  
Wavelet Packet Transform ◽  
Epileptic Seizure Detection ◽  
Scalp Eeg ◽  
Eeg Recordings
Sign in / Sign up

Export Citation Format

Share Document