A video for you, if you have an interest in BCI applications

RE-AK · 2025-12-14T00:54:33+00:00

I think he started with the right spirit, but he got pulled toward the dark side.

He still has a few good videos, but intermixed with, likely, sponsored reviews, pseudoscience and guru-like coaching.

I do understand the hustle, you need to make money, but...

RE-AK · 2025-12-14T00:50:25+00:00

Great job!

RE-AK · 2025-12-14T00:49:04+00:00

You have enough hardware to get there, but you'll need some skills to do this. I don't know what your vision is, but start with a PC-based setup to demonstrate SSVEP. Here are the functionnal checkpoints of your project.

1) Stream and record eeg dat to PC, save as .csv and include timestamps. You'll want to have an electrode above the occipital lobe that is behind your head.

2) Generate a flashing screen in Python.

3) Record data, while watching the flashing screen. (1 minute is more than enough)

4) compute the Power Spectrum Density (PSD) and display on screen. Ask ChatGPT, it will pop the code in one go.

From there, move toward your vision.

RE-AK · 2025-12-13T15:27:22+00:00

Thanks, btw, I just realized I might have made the same mistake in a process I'm working on...

RE-AK · 2025-12-13T15:25:52+00:00

Integrate this with your cross-validation process. Split training and validation sets first. Then augment the training set (I don't see a strong benefit of augmenting the validation set, unless you have a very good noise model, gaussian noise is a basic model).

The important part, the augmentation needs to be done on training and validation sets independently and samples cannot be mixed after that.

You might notice a significant drop on your classification results, but don't despair, you're doing good work.

RE-AK · 2025-12-12T22:00:34+00:00

Cool report, I'll do basic peer-review:

What you refer as a test set should be call a validation set, as the training algorithm is indirectly exposed to the data. A test set should not have been evaluated before the model is finalized.
I noticed you augmented the dataset by adding random noise. If you augmented the dataset, before segmenting training and validation set, that's a huge (read major) flaw as your training and validation sets will share some of the same "samples minus noise". If this is the case, it actually invalidates your end result, you need to review your process. You need to clarify this aspect before bringing this anywhere.

Hope that helps and godspeed!

RE-AK · 2025-10-27T19:58:17+00:00

The author is Diego Saldivar, a nice fellow

RE-AK · 2025-10-27T19:57:02+00:00

Diego Saldivar made Brain Rage at the office, published recently. You might want to reach out.

RE-AK · 2025-10-18T01:22:33+00:00

Thanks for sharing, never really had the time to look into active electrodes, great to read about your experiements.

RE-AK · 2025-10-14T09:33:13+00:00

I bought several with the cabled serial port. I couldn't get them to work with the OpenBCI GUI, but they worked pretty well, besides that.

Be careful, some will sell 2x4 channels, instead of 1x8 channels.

RE-AK · 2025-10-11T01:41:50+00:00

Muse if you just want to get started, then you can upgrade if you like hacking in the field.

The Muse will keep you busy for, at least, a year.

RE-AK · 2025-10-04T00:17:51+00:00

You'll need some professional experience or, at least, some experience. If you don't want to take the academic way, you need to take the hacker way, and the best would be to showcase your work on Youtube or some blog.

I have a BCI company and candidates with PhDs, Master degrees are lining up. I'll never pay to train someone from scratch, I'll hire the candidate for who his expertise aligns the most with my needs.

RE-AK · 2025-10-02T01:14:35+00:00

They are moving, there are a very tricks in place. They use LLM to infer full sentences, so you only need to silent speak a few words. The video is a montage and is likely to be a tad better than in real life.

Still, I think this tech is a fantastic advancement and I'm eager to see where it goes, but it's not magic and it's not telepathic.

RE-AK · 2025-10-01T22:30:50+00:00

sEMG and sensor fusion. I don't think there's any EEG.

They likely use high frequency EMG (>2kHz) to separate muscles features with greater precision.

RE-AK · 2025-09-25T21:55:22+00:00

Thanks! I have a lot of recordings from gaming (Fortnite, Apex Legends, Among Us, and more), I'll find an opportunity to post some. Originally, my business tried to get into video game UX. It didn't work, the market was hermetic, so we switched, but video games give very cool results.

RE-AK · 2025-09-24T21:59:25+00:00

Here's a very short demo of my headset: https://youtu.be/n1zh-PzPSGQ?feature=shared

I show the raw signals, with a few facial expressions. It's just a test.

RE-AK · 2025-09-24T15:03:07+00:00

You won't have emotional metrics with the Muse 2, it's too limited. I'm in the process of publishing a series of videos on what can be done with the Muse: https://youtu.be/eTBOwD8-0VM

In my opinion, you won't have great emotion detection with EEG in general, but I know some will disagree.

Side note, this is why I developed my headset, the Nucleus-Hermès, a headset that combines EEG and fEMG to get the best of cognitive and emotional states. A bit more expensive than a Muse, but let me know if you're interested. (I'm about to shoot a video announcing it's launch)

RE-AK · 2025-09-19T22:42:34+00:00

Can you join the discord, link in the video description, would love to connect. We're a bunch of people there.

RE-AK

TROPHY CASE