# meagmohit/EEG-Datasets

A list of all public EEG-datasets

Repository: https://github.com/meagmohit/EEG-Datasets
Canonical: https://ross.abutalabs.com/products/eeg-datasets
License Family: other
Last push: 2025-10-17T16:17:05+00:00

## Health v2 (maintenance only)
Score: 53/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 47, release rhythm 35, longevity 100
- inputs: {"age_days": 3302, "days_push": 320, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3087, forks 624 (observed 2026-08-28T04:07:42.174124+00:00)

## What it is
A curated list of publicly available EEG (electroencephalography) datasets, covering motor imagery, BCI competitions, and other paradigms. It is a link collection rather than software, maintained as a community-updated resource.

## Use cases
- find public EEG datasets for brain-computer interface research
- locate motor imagery EEG data for machine learning experiments
- download BCI competition datasets
- find EEG data for deep learning model training
- compare EEG datasets by subject count and electrode setup
- find open neuroscience data for signal processing research

## When to choose
- you need to discover open EEG datasets for research or ML projects
- you want a starting point for BCI or neuroscience data exploration

## When to avoid
- you need actual EEG analysis software or processing tools rather than dataset links
- you need a downloadable, versioned dataset rather than a list of external links

## Facets
- artifact type: dataset
- maturity: active
- function: data-science, machine-learning
- domain: machine-learning, healthcare, data-science
- platform: cross-platform
- tags: eeg, awesome-list, bci, neuroscience, curated-links, open-data

## Member repositories
- meagmohit/EEG-Datasets (main) score 53

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:42.174124+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:27:31.695132+00:00, confidence not recorded.
  - readme: https://github.com/meagmohit/EEG-Datasets (fetched 2026-08-28T04:07:42.174124+00:00, sha 3e0874fee51c)
- Data as of 2026-08-30T08:39:29.467469+00:00.