Aashika Reddy

Developing a Machine Learning Algorithm for Seizure Onset Detection and Tailored Music Therapy Inspired by the Mozart Effect for Seizure Reduction

Started Mar. 3, 2025

Abstract or project description

This research aims to develop a machine learning (ML) algorithm for detecting the onset of seizures in real-time. The proposed system will in theory use neural and physiological data (EEG, heart rate) to accurately predict when a seizure is likely to begin, enabling timely intervention. In addition, the algorithm will be integrated with a personalized music therapy component, where songs with effects similar to the Mozart Effect are selected based on the individual's preferences and neurological responses. The goal is to reduce seizure frequency and intensity through auditory stimulation, promoting a non-invasive and natural therapeutic approach. By combining advanced ML techniques with music therapy, this research seeks to enhance seizure management and improve the quality of life for individuals with epilepsy.