The SEED dataset contains subjects' EEG signals when they were watching films clips. The film clips are carefully selected so as to induce different types of emotion, which are positive, negative, and neutral ones.
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An Independent components (IC) dataset containing spatiotemporal measures for over 200,000 ICs from more than 6,000 EEG recordings.
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A multimodal dataset with comprehensive annotations of continuous emotions during naturalistic conversations. The dataset contains multimodal measurements, including audiovisual recordings, EEG, and peripheral physiological signals, acquired with off-the-shelf devices from 16 sessions of approximately 10-minute long paired debates on a social issue.
A multimodal database for eye blink detection and attention level estimation.
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EEG/fMRI Data from 8 subject doing a simple eyes open/eyes closed task is provided on this webpage.
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This dataset includes time-synchronized multimodal data records of students (learning logs, videos, EEG brainwaves) as they work in various subjects from Squirrel AI Learning System (SAIL) to solve problems of varying difficulty levels. The dataset resources include user records from the learner records store of SAIL, brainwave data collected by EEG headset devices, and video data captured by web cameras while students worked in the SAIL products.
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Seizures and seizure-like rhythmic and periodic brain activity known as “ictal-interictal-injury continuum” (IIIC) patterns are frequently detected during brain monitoring with electroencephalography (EEG) in patients with epilepsy or critical illness. Prior efforts to automate detection of IIIC patterns have been limited by lack of large well-annotated datasets to train/evaluate algorithms, and there have been only a few attempts to detect IIIC events other than seizures. The IIIC dataset includes 50,697 labeled EEG samples from 2,711 patients’ and 6,095 EEGs that were annotated by physician experts from 18 institutions. These samples were used to train SPaRCNet (Seizures, Periodic and Rhythmic Continuum patterns Deep Neural Network), a computer program that classifies IIIC events with an accuracy matching clinical experts.
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