Effects of an algorithmically enhanced personalized music-based intervention in patients with dementia

Background Music-based interventions (MBIs) are gaining recognition as non-pharmacological strategies to support individuals with dementia. Rubato is an AI-driven music platform that uses machine learning and deep neural networks to deliver personalized music interventions aimed at reducing stress and anxiety through real-time heart rate variability monitoring. Objective To evaluate a personalized music-based intervention for individuals with mild dementia. Methods In this randomized controlled trial, twenty participants with mild dementia, including Alzheimer's disease, were enrolled, with ten randomly assigned to each of the intervention and control groups. Intervention participants used the Rubato app for 30 minutes daily over 12 weeks, while control participants received standard care. Pre- and post-intervention questionnaires assessed cognition (Mini-Mental State Examination), anxiety (State-Trait Anxiety Inventory), quality of life (Dementia Quality of Life Questionnaire), depression (Geriatric Depression Scale), and memory (Immediate Prose Memory Test). Results Anxiety and depression scores decreased significantly following the MBI in the intervention group compared to controls (p = 0.037 and p = 0.028, respectively). Overall, 80% of the intervention participants showed reduced anxiety compared to 30% of controls, and 70% showed reduced depression compared to 20% of controls. No statistically significant differences were found in cognition, quality of life, or memory, although trends toward improvement were noted in the intervention group. Conclusions These preliminary findings suggest that Rubato's MBI may reduce anxiety and depression in individuals with dementia, with clinically meaningful benefits despite limited statistical power. Larger studies with longer follow-up are needed to validate these findings and further examine effects on cognition and quality of life.