Classification of focal and nonfocal EEG signals using ANFIS classifier for epilepsy detection
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Summary
A computer aided automatic detection and classification method for focal and nonfocal EEG signal classification is presented and the experimental results are presented to show the effectiveness of the proposed classification method.
- Type
- article
- Published
- 2016-12-01
- Cited by
- 62
- References
- 31
- OpenAlex
- https://openalex.org/W2561617417
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:28216731
Keywords
Computer science, Electroencephalography, Artificial intelligence, Classifier (UML), Pattern recognition (psychology)
References
- Patient-Specific Early Seizure Detection from Scalp EEG
- Signal Decomposition Methods for Reducing Drawbacks of the DWT
- Empirical Mode Decomposition Based Classification of Focal and Non-focal Seizure EEG Signals
- [11C]Flumazenil Positron Emission Tomography Visualizes Frontal Epileptogenic Regions
- Automatic identification of epilepsy by HOS and power spectrum parameters using EEG signals: A comparative study
- SPECT in the localisation of extratemporal and temporal seizure foci.
- Performance analysis of support vector machines classifiers in breast cancer mammography recognition
- Automated seizure detection using a self-organizing neural network.
- Epileptic seizure detection using DWT based fuzzy approximate entropy and support vector machine
- Seizure detection using a self-organizing neural network: validation and comparison with other detection strategies.
- Epileptogenic focus detection in intracranial EEG based on delay permutation entropy
- Detection of Epileptic Seizure Event and Onset Using EEG
- The detection of epileptic seizure signals based on fuzzy entropy.
- State-dependencies of learning across brain scales
- Detection of epileptiform activity in EEG signals based on time-frequency and non-linear analysis
- Seizure Detection in Temporal Lobe Epileptic EEGs Using the Best Basis Wavelet Functions
- EEG signal classification using wavelet feature extraction and a mixture of expert model
- Application of Entropy Measures on Intrinsic Mode Functions for the Automated Identification of Focal Electroencephalogram Signals
- Influenza and Other Respiratory Viruses Involved in Severe Acute Respiratory Disease in Northern Italy during the Pandemic and Postpandemic Period (2009–2011)
- CLASSIFICATION OF EEG SIGNALS FOR DETECTION OF EPILEPTIC SEIZURES BASED ON WAVELETS AND STATISTICAL PATTERN RECOGNITION
Cited by
- Noisy EEG signals classification based on entropy metrics. Performance assessment using first and second generation statistics
- Epileptic seizure detection by combining robust‐principal component analysis and least square‐support vector machine
- Influence of differential features in focal and non-focal EEG signal classification
- Focal and Non-Focal Epilepsy Localization: A Review
- Characterization of focal EEG signals: A review
- Neural correlates of action video game experience in a visuospatial working memory task
- A NEW TECHNIQUE FOR CLASSIFICATION OF FOCAL AND NONFOCAL EEG SIGNALS USING HIGHER-ORDER SPECTRA
- Robust Approach Based on Convolutional Neural Networks for Identification of Focal EEG Signals
- Computer aided automated detection and classification of brain tumors using CANFIS classification method
- Distinguishing mental attention states of humans via an EEG-based passive BCI using machine learning methods
- An automated methodology for the classification of focal and nonfocal EEG signals using a hybrid classification approach
- Discrimination of Focal and Non-Focal Seizures From EEG Signals Using Sliding Mode Singular Spectrum Analysis
- Study of EEG Signal for Epilepsy Detection and Localization Using Bagged Tree and SVM Algorithms
- Time-Frequency Domain Deep Convolutional Neural Network for the Classification of Focal and Non-Focal EEG Signals
- Automatic focal and non-focal EEG detection using entropy-based features from flexible analytic wavelet transform
- Automated focal EEG signal detection based on third order cumulant function
- Classification of Focal and Non-Focal Epileptic Patients Using Single Channel EEG and Long Short-Term Memory Learning System
- Detection of Focal and Non-Focal Electroencephalogram Signals Using Fast Walsh-Hadamard Transform and Artificial Neural Network
- Detection and classification of electroencephalogram signals for epilepsy disease using machine learning methods
- Detection of Focal EEG Signals Employing Weighted Visibility Graph
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