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Brain Speeddial Eeg Jev

Offline prototype replaying public Shin 2017 EEG sample-by-sample to trigger intents, gate actions with a Jev policy question, and confirm via repeat or imagery before a mock agent acts.

Stars
1
Language
Python
License
MIT
Published by
Community
Author
AshwaniKottapalli
Last verified
Oct 2026

Can EEG drive an AI agent? Public-data experiments: mental-command detection, Muse-like channel ablation, Jev (typesafe.ai) integration, two-layer EEG confirmation.

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0
Last pushed
Updated Sep 2026

Repo stats from the GitHub API, cached Oct 2026.

About this project

An offline, end-to-end prototype of a "brain speed-dial" for AI agents, built entirely on public EEG datasets replayed sample-by-sample as if they were coming from a headset. No live hardware was used anywhere in this repo.

Quoted from the project's README. Read the full README.

Highlights

  • Replays held-out Shin 2017 trials through a Riemannian decoder with consecutive-window streak detection.
  • Sends Jev only action, cost, and context, turning answers into fire, confirm, or ignore decisions.
  • Measures duplicates, accidentals per idle hour, and latency across none, repeat, and imagery modes.
  • Runs via run_demo.sh with rule fallback, simulated context flags, and headless metrics across folds.

Watch out

Offline prototype with no live headset; context is simulated and agent actions are mock text logs that order nothing. Copy reviewed against the repository README on 2026-10-04, not from running it.

Questions about this entry

Short answers drawn from the linked project or page.

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