"Brain Symphony" is a paper I published in European Neurology (2020), aimed at converting brainwaves (EEG) into music by incorporating cultural artifacts.

https://karger.com/ene/article-abstract/83/5/468/126504/A-Novel-Method-for-Sleep-Stage-Classification?redirectedFrom=fulltext

The sonification of brainwaves is performed on sleep EEG signals, with the tempo varying according to the brain's active and calm states during sleep stages.

This generative art project stands out in terms of its signal processing techniques, MATLAB programming, and the use of a pre-trained Recurrent Neural Network (RNN) trained on Tanbour Maqams.

In this NFT, an EEG signal specific to one minute of sleep in the Slow Wave Sleep (SWS) is converted into musical notes through a mapping process. These notes are then fed into the pre-trained RNN, resulting in the AI model's improvisation based on the Tanbour Maqams.

Y-Axis: Amplitude of EEG Signals in SWS
X-Axis: 256*60=15360 Samples in One Minute