Cortex Mark IV EEG head and Arduino for controlling fingers movement
Haleem
Saudi Arabia
I want to connect the Cortex Mark IV EEG headset to a prosthetic arm for controlling fingers using Arduino. I am new to this field. I have managed the connectivity of Cyton+headset with a dongle, and now I can see the brainwaves in OpenBCI GUI. But now, I cannot interpret which waves are used for finger movements. Secondly, I want to control the prosthetic arm using EEG signals, for which I need to connect Arduino to the laptop. But I don't know the procedure of connecting it. I would really appreciate it if someone could help me to get a start on this. Thanks in advance
Comments
Haleem, hi.
Arduino boards are underpowered for DSP digital signal processing. You would be better off with something like a Raspberry Pi, then you can plug the dongle directly into the Pi.
Then at that point you can use the Brainflow library for receiving the brainwaves and doing any processing you want.
https://brainflow.org/
https://brainflow.readthedocs.io/en/stable/Examples.html#python
To be honest, detecting finger motion is NOT a commonly used BCI paradigm. It is extremely difficult to pickup from EEG. Some advanced research groups are working with it, but not with modest cost equipment. A better strategy would be using some type of VEP visually evoked potentials. A free package called MindAffect uses a form of VEP called cVEP, code based VEP. There are a number of threads here on the forum linking to it.
https://www.google.com/search?as_q=mindaffect&as_sitesearch=openbci.com
Regards, William
You may want to look at this wrist-band device using EMG detection.
https://tech.facebook.com/reality-labs/2021/3/inside-facebook-reality-labs-wrist-based-interaction-for-the-next-computing-platform/
It's not a product, but OpenBCI can easily do EMG detection. This would not be using EEG.
The Facebook wrist device is unusual and likely hard to replicate. The EMG approach would use sensors on the forearm at the specific muscle locations for the fingers of interest.
See some of these images,
https://www.google.com/search?q=forearm+emg+locations+finger+muscles&sclient=img&udm=2