86 datasets found

The Temple University Hospital EEG Seizure corpus (TUSZ) v1.5.2 is a publicly available seizure corpus to date with 5, 612 EDF files, 3, 050 annotated seizures from clinical...

The EEGEyeNet dataset contains 47 hours of high-density 128-channel EEG data synchronized with eye-tracking recordings from 356 healthy adults.

Deep learning and insomnia: assisting clinicians with their diagnosis

Insomnia Identification via Electroencephalography

The OpenBMI dataset is a large benchmark containing 2 sessions of 2-class MI-EEG data (left hand, right hand) from 54 right-handed healthy subjects.

Emotions recognition using EEG signals: A survey.

EEG-based emotion recognition often requires sufficient labeled training samples to build an effective computational model. Labeling EEG data, on the other hand, is often...

EEG dataset for anterior jaw lobectomy

Preterm EEG data set for inter-burst detection

EEG dataset for sleep staging task

EEG dataset for sleep staging task

The Sleep Heart Health Study (SHHS) dataset contains polysomnography (PSG) recordings from home-based devices with supervision from specialized technicians.

The MEG and EEG dataset used in this paper for source imaging.

The UCI EEG dataset consists of EEG signals from two groups of subjects - alcoholic individuals and controls. The dataset has three attributes: alcoholism, stimulus condition,...

The dataset is used to study the neuronal dynamics underlying electroencephalograms (EEG) and to recover arrhythmic EEG transients from their stochastic interference.

The dataset used in this paper is a collection of EEG signals recorded from 6 healthy males using dry electrodes. The dataset is used for training and testing a convolutional...

A large and rich EEG dataset for modeling human visual object recognition.

This public dataset was published by Mumtaz et al. It consists of EEG recordings from 34 MDD patients and 30 HCs.

EEG Synthetic Data Generation Using Probabilistic Diffusion Models

ERP-based EEG detection gaining increasing attention in the field of brain-computer interfaces. However, due to the complexity of ERP signal components, their low...