EEGUnity
importeddata/eegunity
An open source tool for large-scale EEG datasets processing
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Data & Standards
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- active
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- baizhige.github.io/EEGUnity/
- Repository
- github.com/Baizhige/EEGUnity
- Documentation
- unknown
- Tags
- dataset-manager · eeg · eeg-dataset · eeg-signals-processing · large-dataset · large-language-model · large-multimodal-models · python-library
- Regulatory
- unknown
Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- 3.eeg_recognationeeg · eeg-dataset · eeg-signals-processing
Machine learning for Anonymous detection of an alcoholic by EEG signals
- hu-neuro-pipelineeeg · eeg-signals-processing · python-library
Single trial EEG pipeline at the Abdel Rahman Lab for Neurocognitive Psychology, Humboldt-Universität zu Berlin
- phyaateeg · eeg-dataset
PhyAAt: Physiology of Auditory Attention - Processing Library
- Sans-Tracaseeg · eeg-dataset
An Interactive Cross-Platform tool to run Online EEG Experiments using Web-Bluetooth and the Muse EEG headset.
- The NMT Scalp EEG Dataset: An Open-Source Annotated Dataset of Healthy and Pathological E…eeg-dataset
Dataset Overview The NMT Scalp EEG Dataset is an open source collection of 2,417 anonymised scalp electroencephalogram recordings obtained from unique participants. The collection contains…
- DrugGenlarge-language-model
DrugGen: Advancing Drug Discovery with Large Language Models and Reinforcement Learning Feedback
- api.github.com/repos/Baizhige/EEGUnityretrieved 2026-08-25 · via github-api
Machine-imported from GitHub search. Last push 2026-08-19, 76 stars, license reported as NOASSERTION. Category and schematic were assigned by keyword heuristics and are unreviewed. GitHub reported NOASSERTION; the licence was read from the LICENSE file as MIT, because GitHub's detector does not recognise open hardware licences.
Not yet verified by a human. Correct this record →
/v1/entries/61.json→ .entries["eegunity"]
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