Seizure Detection in Temporal Lobe Epileptic EEGs Using the Best Basis Wavelet Functions
Explore this paper's citation graph
Summary
A novel method using best basis wavelet functions and double thresholding that can be used in clinical studies as an automatic decision support tool and reduce the physician’s workload and provide accurate diagnosis of epileptic seizures is proposed.
- Type
- article
- Published
- 2010-08-01
- Cited by
- 28
- References
- 22
- OpenAlex
- https://openalex.org/W2078428371
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:26174249
Keywords
Ictal, Epilepsy, Computer science, Electroencephalography, Thresholding
References
- Automatic recognition of epileptic seizures in the EEG.
- Electroencephalography: Basic Principles, Clinical Applications and Related Fields
- EEG in the diagnosis, classification, and management of patients with epilepsy
- Book Review: Electroencephalography: Basic Principles, Clinical Applications and Related Fields, ed 2, edited by Ernst Niedermeyer and Fernando Lopes da Silva. Published in 1987 by Urban & Schwarzenberg, Baltimore, 940 pages, $110.00
- A Radial Basis Function Neural Network Model for Classification of Epilepsy Using EEG Signals
- EEG signal classification using wavelet feature extraction and a mixture of expert model
- Seizure prediction: the long and winding road.
- Approximate Entropy-Based Epileptic EEG Detection Using Artificial Neural Networks
- Mixed-Band Wavelet-Chaos-Neural Network Methodology for Epilepsy and Epileptic Seizure Detection
- Analysis of EEG records in an epileptic patient using wavelet transform.
- Wavelet preprocessing for automated neural network detection of EEG spikes
- From wavelets to adaptive approximations: time-frequency parametrization of EEG
- A multistage, multimethod approach for automatic detection and classification of epileptiform EEG
- De-noising by soft-thresholding
- Ideal spatial adaptation by wavelet shrinkage
- Epileptic seizure prediction and control
- Analysis of brain function and classification of sleep stage EEG using daubechies wavelet
- American Electroencephalographic Society guidelines for standard electrode position nomenclature
- Electroencephalography—Basic principles, clinical applications and related fields
- Neural network detection of epileptic seizures in the electroencephalogram
Cited by
- Simulating and predicting river discharge time series using a wavelet‐neural network hybrid modelling approach
- Optimal features for online seizure detection
- Classification of Cardiac Arrhythmias using Biorthogonal Wavelets and Support Vector Machines
- Wavelet-based EEG processing for computer-aided seizure detection and epilepsy diagnosis.
- Quickest seizure onset detection in drug-resistant epilepsy
- Quickest detection of drug-resistant seizures: An optimal control approach
- Review: A Survey of Performance and Techniques for Automatic Epilepsy Detection
- Classification of focal and nonfocal EEG signals using ANFIS classifier for epilepsy detection
- Selecting Statistical Characteristics of Brain Signals to Detect Epileptic Seizures using Discrete Wavelet Transform and Perceptron Neural Network
- Whole brain epileptic seizure detection using unsupervised classification
- Symbolic time series analysis of electroencephalographic (EEG) epileptic seizure and brain dynamics with eye-open and eye-closed subjects during resting states
- EEG-based tonic cold pain recognition system using wavelet transform
- A comprehensive analysis of support vector machine and Gaussian mixture model for classification of epilepsy from EEG signals
- Automatic Epilepsy Detection Based on Wavelets Constructed From Data
- Automatic Detection of Epileptic Seizures in EEG Using Sparse CSP and Fisher Linear Discrimination Analysis Algorithm
- Identification of epileptic discharge based on statistical analysis and fractal analysis
- A Scoping Review of Artificial Intelligence Algorithms in Clinical Decision Support Systems for Internal Medicine Subspecialties
- Epileptic EEG signal classifications based on DT-CWT and SVM classifier
- Automatic epileptic seizure detection in EEG signals using sparse common spatial pattern and adaptive short-time Fourier transform-based synchrosqueezing transform
- Classification of Epileptic Seizures by Simple Machine Learning Techniques: Application to Animals’ Electroencephalography Signals
Related papers
- Global Thresholding and Multiple-Pass Parsing
- CHILDREN WITH INTRACTABLE FOCAL EPILEPSY: ICTAL AND INTERICTAL 99TcVi HMPAO SINGLE PHOTON EMISSION COMPUTED TOMOGRAPHY
- A localized thresholding method based on boundary detection
- Clinical significance of ictal high frequency oscillations in medial temporal lobe epilepsy.
- Speech Preservation during Language‐dominant, Left Temporal Lobe Seizures: Report of a Rare, Potentially Misleading Finding
- Interictal regional slow activity in temporal lobe epilepsy correlates with lateral temporal hypometabolism as imaged with18FDG PET: neurophysiological and metabolic implications
- Presurgical evaluation of temporal lobe epilepsy using interictal temporal spikes and positron emission tomography.
- Dipole source localization of interictal epileptiform activity in temporal lobe epilepsy with medial temporal lesion
- The Hippocampus and Cortex Together Generate the Scalp EEG Ictal Discharge in Temporal Lobe Epilepsy