On-the-edge processing of EEG signals for motor imagery tasks recognition

Abstract

The development of brain-computer interfaces aims to enable communication between humans and machines, mainly through devices capable of acquiring and interpreting the electrical signals emitted by the user's brain when carrying out specific and intentional actions. This work presents the implementation on an FPGA of a compact convolutional neural network capable of correctly classifying this type of signals.