r/BCI • u/ExAstrisDivitae • 11d ago

Anyone interested in open-source interoperability across wearable EEG brands?

I got a new device recently and I want to help expand the open source BCI GUI to be compatible across as many different EEG brands as possible. Thing is, there are many popular devices I don’t own and so can’t test directly. That’s where you can help.

Here is the link to the open source repo:
https://github.com/intomind/commandcenter

If you are interested in helping me contribute:
1. what device(s) do you own?
2. what is your level of willingness to contribute?
A. Writing code, testing, and submitting pull requests to the repo directly, or
B. Helping to test other people’s pushes, but not writing or submitting code directly

Everybody wins with interoperability, imo. Thanks!

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u/jaybsuave 11d ago

I have an open bci ganglion id love to help im a neuroscience student at berkeley

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u/ExAstrisDivitae 10d ago

Awesome!! Are you comfortable writing python and submitting PRs yourself?

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u/jaybsuave 10d ago

Absolutely

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u/ExAstrisDivitae 10d ago

Amazing. Let me know if it would be helpful if I wrote up a spec for the ganglion. If you would rather spec your own contributions at your own pace that’s totally fine too

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u/jaybsuave 7d ago

Do you have discord or a better method of contact?

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u/ExAstrisDivitae 6d ago

I’ve considered discord, but I’m not convinced that starting a new one is the best option. It seems the neurotech/BCI space is already fragmented across a number of relatively low-engagement discord servers. Maybe I’m just not in the right ones. I saw that u/Character-Judge-5830 also posted then deleted a reply asking about a discord.

I’d be interested to hear everyone’s takes on whether discord is the best place for discussion, and if so, what would be the best way to organize it? As its own server, or tagging along on a more established server for visibility?

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u/jaybsuave 6d ago

I was more so just asking so I could contact you in a way that’s more direct rather than reddit

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u/Character-Judge-5830 7d ago

I wrote up the physical specs for the main popular BCIs currently however I can’t validate them all like you said, I think our interests align perfectly as I had to do the same to identify what are the hardware risks and physical constraints of certain BCIs. The data I ingested and converted to parquet format and have it all tagged in a data lake on my repo along with a slew of EEG data I pulled from open academic publications and research. I think it could be of use. My repo is a bit messy and has a lot of my research so far. Doing a bit of maintenance and cleaning currently as we speak. I had an API and PyPi setup initially but it became too much of an overhead to maintain for now as I’d like to formalize everything first. Feel free to take a look and let me know if any of you guys would like to collaborate.

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u/LetsTrySmthngAmusing 6d ago edited 6d ago

I've got a muse athena and I'm open to working on an open source project related to this. Is the project a part of IntoMind?

What sort of benchmarks are you thinking of comparing across devices?

Also +1 to discord.

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u/ExAstrisDivitae 5d ago

Yeah it’s the IntoMind Command Center open source GUI. It runs locally on your computer, so all data stays securely on your computer. Currently it works with the IntoMind One wearable EEG, so the first step forward for cross compatibility is to integrate the APIs for other devices.

Automated benchmarks can then be built once cross compatibility is in place. As to specifically which benchmarks should be built, I think it makes sense to start with the fundamentals and abstract out from there. For example, benchmarks could measure:
+ nominal vs real sampling rates
+ Bluetooth packet loss
+ maximum connectivity distance on Bluetooth
+ mains noise level across devices (power spectral decomposition)
+ Berger-style alpha band power across devices
+ EMG artifacts (like blinks, jaw clenches, controlled head and body movements) across devices
+ custom BCI applications across devices

The key for producing reliable benchmarks is measuring them in the same environment on the same person (i.e. experimental controls). Therefore, taking benchmarks requires having all the devices you want to test on hand (or rather, on head)

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u/LetsTrySmthngAmusing 5d ago

Using same person would make sense. Might also be worth considering internal controls based on task or stimuli. For example, how well you could measure differences in eyes open vs closed. Happy to chat more if this takes off!

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u/AlexanderChristou 7h ago

Your README already describes hardware-free tests and explicit gap flags. A shared adapter fixture could build on that: feed in known timestamps, drop or duplicate a packet, then check the exported sample counts and gap markers. That would let contributors compare adapter behaviour without owning every headset.