Voice analysis of patients with neurological disorders using acoustical and nonlinear tools

In this paper, we analyze voice signals recorded from patients with neurological disorders of different etiologies. The study was based on three samples of each patient: one before any ingestion, one after the swallowing of a liquid solution, and one after the swallowing of a pasty solution. We used three approaches: first, acoustical analysis, specifically fundamental frequency, jitter and shimmer; second, a proposed analysis method of vocal dynamic visual patterns, which are based on phase space reconstruction of the signals; and third, relative entropy analysis between the groups of signals. We show that the acoustical measures were not able to differentiate the study cases, relative entropy was only partially able to perform this task, but the visual patterns analysis was successful.