Sparse Bump Sonification : a New Tool for Multichannel EEG Diagnosis of Brain Disorders

The purpose of this paper is to investigate utilization of music and multimedia technology to create a computational intelligence procedure for EEG multichannel signals analysis that would be of clinical utility to medical practitioners and researchers. We propose here a novel approach based on multi channel sonification, with a time-frequency representation and sparsification process using bump modeling. Specific focus is given to applications in early detection and diagnosis of early stage of Alzheimer’s disease. The fundamental question explored in this paper is whether clinically valuable information, not available from the conventional graphical EEG representation, might become apparent through an audio representation. Preliminary evaluation of the obtained music score – by sample entropy, number of notes, and synchronous activity – show promising results.

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