by Piera Riccio, Francesco Galati , Maria A. Zuluaga , Juan Carlos De Martin, and Stefano Nichele

Summary

This academic paper introduces a novel system that uses artificial intelligence to translate brain activity (EEG signals) into visual art, specifically paintings. The core of the system involves processing EEG data to encode emotional states and then using a generative network to create paintings that visually express those emotions. The researchers emphasise the challenge of formally defining and processing emotions but demonstrate how their human-machine interaction paradigm can result in unique artistic representations of feeling. The findings suggest promising potential for AI technologies in computational creativity and affective computing, opening up new possibilities for artistic expression and therapy.