105 datasets found

The dataset used in the study to analyze the performance of an LSTM-based model using different levels of speech features.

EEG data were collected by 1,000 Hz sampling rate using 64 Ag/AgCl electrodes in the 10/20 international system via BrainAmp (BrainProduct GmbH, Germany).

EEG classification aims to classify EEG recordings that consist of C sensor readings regularly sampled, e.g., at a set frequency in Hz, usually for a short time range of a few...

EEG classification aims to classify EEG recordings that consist of C sensor readings regularly sampled, e.g., at a set frequency in Hz, usually for a short time range of a few...

EEG classification aims to classify EEG recordings that consist of C sensor readings regularly sampled, e.g., at a set frequency in Hz, usually for a short time range of a few...

The proposed method uses two publicly available motor imagery EEG datasets for validation.

The TUH EEG Seizure Corpus (TUSZ) is a publicly available dataset used for research on automatic seizure detection and classification.

Two simultaneous speech EEG recording databases for this work. For database A five female and five male subjects took part in the experiment. For database B five male and three...

EEG dataset for model test (across-modality & across-subject): To further confirm that our ReAlnet-fMRIs learn more general human brain representations instead of just human...

EEG data collected from construction workers for brain-computer interface applications

EEG time series data from nine healthy right-handed subjects, with 200Hz high-density (64-channel) recordings.

Simulated sleep-inspired data to test the robustness of the model, EEG time series with realistic spectral content and temporal dynamics.

The Temple University Hospital EEG Corpus is a large dataset of clinical EEG data used to train and evaluate machine learning models for EEG event classification.

Polysomnographic data from the Sleep-EDF dataset, which contains 197 full-night polysomnographic recordings.

The dataset used in the study on the relationship between mood, sleepiness, and EEG, specifically functional connectivity by 40 Hz monaural beats.

WAY-EEG-GAL dataset is used for motor kinematics prediction analysis. The dataset contains synchronous EEG and hand kinematics data collected during the grasp-and-lift task.

The dataset used in the study of FingerNet, a deep neural network for fine motor imagery classification using EEG signals.

The dataset 2a from BCI competition IV is used to evaluate the proposed method.

The High-Gamma Dataset is a publicly available dataset containing 128-channel EEG recordings of fourteen healthy subjects executing three different movement classes and a...

EEG signals recorded by a 32 active electrodes BrainVision (Brain Products GmhH) equipment during 5 minute sessions, while presenting an auditive stimulus to the subject.