  Artificial intelligence has made significant advances in recent years and
this has had an impact on the field of neuroscience. As a result, different
architectures have been implemented to extract features from EEG signals in
real time. However, the use of such architectures requires a lot of computing
power. As a result, EEG devices typically act only as transmitters of EEG data,
with the actual data processing taking place in a third-party device. That's
expensive and not compact. In this paper, we present a shield that allows a
single-board computer, the Jetson Nano from Nvidia, to be converted into a
brain-computer interface and, most importantly, the Jetson Nano's capabilities
allow machine learning tools to be used directly on the data collection device.
Here we present the test results of the developed device.
https://github.com/HackerBCI/EEG-with-JetsonNano
