u/Empty_Replacement_43

Hi everyone,

We just open-sourced NeuraDock Visual Cognitive Load Agent, a local-first EEG agent that turns EEG data into a real-time cognitive-load API for AI agents, BCI prototypes, HCI/XR systems, and adaptive interfaces.

The idea is simple:

Instead of treating EEG as just offline signal analysis, we want to make it usable as a local API:

EEG file / synthetic replay / NeuraDock hardware
        ↓
preprocessing + signal quality gating
        ↓
alpha dynamics + visual cognitive-load estimation
        ↓
local dashboard + API endpoint
        ↓
AI agents / XR / HCI / neurofeedback apps

A few things we wanted to make clear:

• No hardware required to start: you can run the agent with synthetic replay or example EEG data.

​

git clone https://github.com/Neuradock/eeg-workstation-agent.git
cd eeg-workstation-agent
python -m venv .venv && source .venv/bin/activate
pip install -e ".[dev]"
neuradock-agent serve --port 8765
# open http://127.0.0.1:8765

• Works with hardware too: if you have NeuraDock EEG hardware, it can run as a real-time closed-loop cognitive-load monitor.
• Full toolchain is open-source: data loading, preprocessing, quality control, cognitive-load analysis, dashboard, and API.
• Local-first design: the core signal processing runs locally; the LLM layer is optional and receives summarized outputs rather than raw dense EEG streams.
• Developer-oriented: the goal is to make EEG usable by AI developers, BCI builders, HCI/XR researchers, and open-source hardware communities.

We also wrote a short paper/tutorial explaining the architecture and design choices.

GitHub:
https://github.com/Neuradock/eeg-workstation-agent

Article / tutorial:
https://arxiv.org/html/2606.26518v1

Short demo video:
https://www.youtube.com/shorts/9MWe_rCnWNY

.exe applications:

https://github.com/Neuradock/eeg-workstation-agent/releases/tag/Neuradock_Cognitive_Load_Agent

I’d love feedback from people working on EEG, BCI, neurotech, AI agents, XR/HCI, or adaptive interfaces.

A few questions we’re thinking about:

1. What would be the most useful “killer app” for a real-time cognitive-load API?
2. Would you use this more as a research tool, a developer API, or a hardware demo platform?
3. What integrations would make this more useful: OpenClaw, Claude Code/Codex workflows, Unity, Unreal, browser extension, VS Code, or something else?

Happy to hear criticism too. We’re trying to make EEG more accessible and useful for developers, not just for offline neuroscience analysis.

Body:

Hi r/EEG,

We are the NeuraDock. We’ve been building a 7-channel dry-electrode EEG dev kit, and today we’re open-sourcing the full developer toolchain on GitHub. Not just a single repo with some scripts — the entire pipeline from data acquisition to analysis.

The problem we kept hitting

If you’ve ever prototyped with EEG, you know the drill: buy hardware → discover the data format is locked → write your own parser → build preprocessing from scratch → want to validate the hardware with a quick demo → no public datasets exist → realize the hardware interface specs aren’t open either, so third-party integration means reverse-engineering.

We got tired of spending two weeks on infrastructure before spending one day on the actual experiment. So we built the infrastructure upfront and open-sourced it.

What’s actually open

We split the project into 8 repos, each covering a distinct layer:

表格

Repository	What it does
eeg-workstation	Project overview and navigation
eeg-workstation-software	Recording software releases
eeg-workstation-docs	Getting started, data format, FAQ, hardware interface notes
eeg-workstation-python	Python tools, notebooks, data reading examples
eeg-workstation-examples	Ready-to-run demos: eyes open/closed, PSD, band power, SSVEP, cVEP, signal quality, real-time markers
eeg-workstation-data	Public sample datasets — you can run code without buying hardware
eeg-workstation-hardware	Hardware interface and port specs for third-party integration
eeg-workstation-agent	(in development) Natural-language EEG workflows

Three entry points, depending on where you are

https://preview.redd.it/00ho7zjqus6h1.png?width=1939&format=png&auto=webp&s=4b7b0d6d28cc02886900d8e3e0c1de20f911c3a8

Path A: No hardware yet

1. Grab sample data from eeg-workstation-data
2. Run the reading examples in eeg-workstation-python
3. Reproduce PSD / band power analysis from eeg-workstation-examples → Validate your algorithm before you buy anything.

Path B: You have the hardware

1. Follow the setup guide in eeg-workstation-docs
2. Record with the software from eeg-workstation-software
3. Read your local data with eeg-workstation-python and run the examples → Full acquisition-to-analysis loop.

Path C: You’re building a product

1. Check the hardware interface specs in eeg-workstation-hardware
2. Integrate via UART/BLE into your own system
3. Use eeg-workstation-python as your backend analysis engine → Embed EEG into your product.

On hardware openness

We’re releasing the hardware interface and port specifications — physical connectors, communication protocol, data frame format. This lets you integrate the NeuraDock acquisition module into your own stack or build compatible extensions.

Full schematics, PCB files, and manufacturing files are not in this release. We’re treating NeuraDock first as an extensible platform, second as an open hardware project. We want to make integration easy before we release deeper hardware design.

What’s next

The current release solves “how do developers efficiently use EEG.” Next, we’ll add a natural-language interaction layer on top of this same toolchain — so non-programmers (clinicians, PMs, researchers who don’t code) can upload data and get analysis reports through conversation.

For now, the toolchain is live. The agent is coming.

Links

• GitHub: github.com/Neuradock
• Community: Discord (search NeuraDock Community)
• Youtube: https://www.youtube.com/@NeuraDock/videos
• HACKDAY.IO: https://hackaday.io/project/205753-neuradock-a-hackable-7-channel-eeg-workstation

Happy to answer questions or take feedback on the repo structure. If you try the examples and hit issues, open a GitHub issue — we’re monitoring.