Investigating the effect of singing in individuals with psychiatric disorders or mental conditions

The effect of music on the human brain is well established, yet the specific impact of singing and vocalizing on psychiatric or mental disorders remains underexplored. Using machine learning, this project aims to decode the interaction between vocalization and brain activity, as recorded through EEG and other non-invasive techniques.

Patients will participate in guided singing sessions exploring vocal parameters such as pitch, intensity, timbre, rhythm, articulation, breath control, and emotional expression. Data will include pre- and post-session questionnaires, EEG signals, and recorded vocal features. A multimodal machine learning model will be developed to integrate these datasets and identify both beneficial and adverse effects of singing on brain function.

The goal is to design personalized music therapy protocols, supported by AI-driven feedback, with potential integration into clinical practice. Future directions include longitudinal studies and broader applications for improving the mental health and wellbeing of patients with mental or psychiatric conditions.

Funded by MARTINA