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Multiscale Entropy Analysis of EEG Signals
Electroencephalogram (EEG) contains a lot of pathological information, which is the most effective clinical tool for detecting epileptic seizure. In...
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A combinational deep learning approach for automated visual classification using EEG signals
According to the literature, electroencephalographic (EEG) data are among the most important physiological signals, and EEG classification has...
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Enhanced Epileptic Seizure Detection Through Graph Spectral Analysis of EEG Signals
Epilepsy is a persistent health condition marked by unusual and highly synchronized electrical activity in the brain cells, resulting in recurring...
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LieWaves: dataset for lie detection based on EEG signals and wavelets
This study introduces an electroencephalography (EEG)-based dataset to analyze lie detection. Various analyses or detections can be performed using...
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Merged CNNs for the classification of EEG motor imagery signals
The using of Electroencephalography (EEG) signals for motor imagery (MI) has recently gained significant attention due to their remarkable ability to...
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SPINDILOMETER: a model describing sleep spindles on EEG signals for polysomnography
This paper aims to present a model called SPINDILOMETER, which we propose to be integrated into polysomnography (PSG) devices for researchers focused...
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Classification for EEG Signals Using Machine Learning Algorithm
Electroencephalography (EEG) is a non-invasive technique that is used to record the electrical activity of the brain. EEG signals are widely used in...
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Decoding emotional patterns using NIG modeling of EEG signals in the CEEMDAN domain
Electroencephalogram (EEG) signals used for emotion classification are vital in the Human–Computer Interface (HCI), which has gained a lot of focus....
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Automatic classification of seizure and seizure-free EEG signals based on phase space reconstruction features
Epilepsy is a type of brain disorder triggered by an abrupt electrical imbalance of neuronal networks. An electroencephalogram (EEG) is a diagnostic...
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Transfer learning based epileptic seizure classification using scalogram images of EEG signals
Epilepsy is a common neurological disorder that occurs due to an abnormality of the nerve cells in the brain. Electroencephalogram (EEG) analysis is...
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Shifted and Weighted LFCC Features for Hand Movements Recognition Using EEG Signals
The Brain computer interface (BCI) technology attracts many researchers due to its vital applications in medicine and biomedical domains. Decoding...
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Detection of Epileptic Seizure from EEG Signals Using Majority Rule Based Local Binary Pattern
In recent days, local binary pattern and their variants plays a vital role in classification of EEG signals. Hence, in this paper a novel method for...
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LSTMNCP: lie detection from EEG signals with novel hybrid deep learning method
Lying has become an element of human nature. People lie intentionally or unintentionally at any point in their lives. Human beings can deceive by...
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AN efficient deep learning with an optimization framework to analyse the eeg signals
Electroencephalogram (EEG) signals can offer a mode to communicate with the humans and outside world. Also, the human brain is negatively affected...
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Performance investigation of epilepsy detection from noisy EEG signals using base-2-meta stacking classifier
Epilepsy is a chronic neurological disease, characterized by spontaneous, unprovoked, recurrent seizures that may lead to long-term disability and...
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Epileptic seizure detection using scalogram-based hybrid CNN model on EEG signals
Epilepsy is one of the most usual neurological diseases characterized by abnormal brain activity, resulting in seizures or strange behavior,...
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Emotion Recognition from Electroencephalogram (EEG) Signals Using a Multiple Column Convolutional Neural Network Model
Emotions are vital in human cognition and are essential for human survival. Emotion is often associated with smart decisions, interpersonal behavior,...
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Detecting emotions through EEG signals based on modified convolutional fuzzy neural network
Emotion is a human sense that can influence an individual’s life quality in both positive and negative ways. The ability to distinguish different...
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Classification of arithmetic mental task performances using EEG and ECG signals
In this study, a classification is done for electroencephalogram (EEG) and electrocardiogram (ECG) records belong to arithmetic tasks with good and...
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A robust semi-supervised deep learning approach for emotion recognition using EEG signals
Many deep learning models are recently proposed for Electroencephalography (EEG) classification tasks. However, they are full-supervised and require...
