With the help of PiEEG, a custom add-on board, up to eight electroencephalography (EEG) signals can be read in real-time
A few months ago, researchers at Brown University introduced a new concept for Brain-Computer interfaces or BCIs, allowing it to monitor a larger group of brain cells.
Inspired by the promise that BCIs hold for enabling control of IoT devices using one’s mind, one of our DIY team members created an innovative BCI device.
Although BCI research has been promising, the ongoing global chip shortage has proved to be a setback for any immediate implementation or development of BCI technology. At the same time, there is a lack of appropriate signal processing software for reading signals, which can be incorporated into a low-cost BCI device.
Now, adding to the development of BCIs is a new concept proposed by two researchers, Ildar Rakhmatulin and Sebastian Volkl.
Being involved in the study and improvement of neural networks and machine vision for quite some time, they aim to get rid of highly expensive hardware for brain mapping functions and have thus devised a BCI system that uses Raspberry Pi.
With the help of PiEEG, a custom add-on board that was mounted over a Raspberry Pi 3, and which used C, C ++ and Python, was able to read up to eight electroencephalography (EEG) signals in real-time, collected in the brain by electrodes placed in a cap. The control of exoskeletons is also one of the proposed uses.
Besides Raspberry Pi 3, the PiEEG is also compatible with a Raspberry Pi 4 and can be connected through the GPIO pins. There are strict requirements that must be met for this to work, including isolation from noise generated by the AC power supply
The PiEEG intends to be launched soon via a Crowd Supply Campaign on the hackerBCI platform that was started for providing easy access to neuroscience projects and experiments.