54 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).

The WithMe dataset contains EEG signals from subjects performing an auditory-visual attention task.

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

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...

Synthetic EEG data generated using Generative Adversarial Networks

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.

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

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

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...

A large-scale multi-modal dataset comprising 1 million EEG-image-text pairs.

Human EEG data were obtained from an EEG open dataset, THINGS EEG2 (Gifford et al., 2022), including EEG data from 10 healthy human subjects in a rapid serial visual...

The dataset used in this study is a collection of EEG signals from individuals with Autism Spectrum Disorder (ASD) and typically developing individuals.

The dataset used in this study is a collection of EEG signals from individuals with Autism Spectrum Disorder (ASD) and typically developing individuals.

Autism Spectrum Disorder (ASD) is a developmental disorder that often impairs a child’s normal development of the brain. EEG measures the electric signals of the brain via...

A large-scale clinical EEG dataset for Deep Learning

Emotion recognition based on Electroencephalography (EEG) has gained significant attention and diversified development in fields such as neural signal processing and affective...