Sintetización de una red neuronal convolucional en microcontrolador para la identificación de gestos mediante el procesamiento de señales electroencefalográficas

Abstract

The ability to interpret electroencephalographic (EEG) signals for gesture identification represents a significant advance in brain-computer interface and biometric control applications. This degree project entitled "Synthesizing a Convolutional Neural Network on Microcontroller for Gesture Identification by Processing Electroencephalographic Signals". It explores the feasibility of miniaturizing and optimizing a convolutional neural network (CNN) for execution on a low-power microcontroller, the Arduino Nano 33 BLE, an emerging device in the field of embedded computing and IoT.