EEG seizure detection and prediction algorithms: a survey
Epilepsy patients experience challenges in daily life due to precautions they have to take in
order to cope with this condition. When a seizure occurs, it might cause injuries or endanger …
order to cope with this condition. When a seizure occurs, it might cause injuries or endanger …
Epileptic seizure classification in EEG signals using second-order difference plot of intrinsic mode functions
RB Pachori, S Patidar - Computer methods and programs in biomedicine, 2014 - Elsevier
Epilepsy is a neurological disorder which is characterized by transient and unexpected
electrical disturbance of the brain. The electroencephalogram (EEG) is a commonly used …
electrical disturbance of the brain. The electroencephalogram (EEG) is a commonly used …
Classification of ictal and seizure-free EEG signals using fractional linear prediction
In this paper, we present a new method for electroencephalogram (EEG) signal
classification based on fractional-order calculus. The method, termed fractional linear …
classification based on fractional-order calculus. The method, termed fractional linear …
Empirical mode decomposition based classification of focal and non-focal EEG signals
R Sharma, RB Pachori… - … Conference on Medical …, 2014 - ieeexplore.ieee.org
The electroencephalogram (EEG) signals are commonly used signals for detection of
epileptic seizures. In this paper, we present a new method for classification of two classes of …
epileptic seizures. In this paper, we present a new method for classification of two classes of …
Classification of seizure and seizure-free EEG signals using multi-level local patterns
TS Kumar, V Kanhangad… - 2014 19th International …, 2014 - ieeexplore.ieee.org
This paper introduces a new discriminant feature-Multi-level local patterns (MLP) for
classification of seizure and seizure-free electroencephalogram (EEG) signals. The …
classification of seizure and seizure-free electroencephalogram (EEG) signals. The …
[PDF][PDF] An artificial neural network model for classification of epileptic seizures using Huang-Hilbert transform
SJ Husain, KS Rao - International Journal on Soft Computing, 2014 - academia.edu
Epilepsy is one of the most common neurological disorders characterized by transient and
unexpected electrical disturbance in the brain. In This paper the EEG signals are …
unexpected electrical disturbance in the brain. In This paper the EEG signals are …
A fully automatic ocular artifact removal from EEG based on fourth-order tensor method
S Ge, M Han, X Hong - Biomedical Engineering Letters, 2014 - Springer
Purpose The aim of this paper is to propose a fully automatic system using the
underdetermined blind source separation (UBSS) method and kurtosis to remove ocular …
underdetermined blind source separation (UBSS) method and kurtosis to remove ocular …
Analysis of epileptic seizure EEG signals using reconstructed phase space of intrinsic mode functions
Epilepsy is a neurological disorder of the brain. The electroencephalogram (EEG) signals
are commonly used to detect the epileptic seizures which are the result of abnormal …
are commonly used to detect the epileptic seizures which are the result of abnormal …
Speaker identification using empirical mode decomposition-based voice activity detection algorithm under realistic conditions
MS Rudramurthy, NK Pathak, VK Prasad… - Journal of Intelligent …, 2014 - degruyter.com
Speaker recognition (SR) under mismatched conditions is a challenging task. Speech signal
is nonlinear and nonstationary, and therefore, difficult to analyze under realistic conditions …
is nonlinear and nonstationary, and therefore, difficult to analyze under realistic conditions …