PhysioNet 2018 Challenge: Sleep Arousal Detection PSG (Training)
…994 subjects (with expert annotations) - Test set: 989 subjects (PSG signals only…
- Participants
- 1983
- Channels
- 6 (other)
- Citations
- 91
- Size
- 401 GB
- Version
- v1.1.0
- Updated
- Jul 10, 2026
100 results for "seizure annotation" · page 4 of 10 · ranked by relevance
…994 subjects (with expert annotations) - Test set: 989 subjects (PSG signals only…
A high-density 124-channel EEG dataset comprising event-related potentials (ERPs) from 10 healthy participants during a visual object recognition task. Participants viewed 5,184 photographs from six object categories (human body, human face, animal body, animal face, fruit/vegetable, and inanimate objects), with 72 photographs per category, presented for 500 ms each. The dataset is suitable for investigating neural representations of object categories through single-trial EEG classification and representational similarity analysis.
[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on004843-blue…
…rich linguistic annotations for the stimuli, including word frequencies, part-of-speech…
…Labels from the second scorer, when present, are stored in annotation extras…
Imported from OpenNeuro ds003825
…The annotation labels in the EDF map directly to the value levels…
TMNRED is an EEG dataset collected from 30 healthy, right-handed native Chinese speakers performing a natural reading task designed to investigate fuzzy semantic target identification. Participants read Chinese news headlines and short sentences containing target and non-target semantic items while EEG was recorded across 8 blocks of 400 trials each. The dataset supports research into semantic processing mechanisms during naturalistic reading in the Chinese language.
…Events and Linguistic Annotations --------------------------------- The scientific value of this dataset is the…
This dataset comprises 64-channel EEG recordings and behavioural ratings from 47 participants who read and evaluated 210 short English-language texts, including Haiku, Senryu, and non-poetic Control texts. Each text was rated on five subjective dimensions: Aesthetic Appeal, Vivid Imagery, Being Moved, Originality, and Creativity. The dataset supports research into the neural and cognitive processes underlying aesthetic and creative engagement with poetic language, and includes resting-state EEG segments recorded before and after the experimental session.