Characterizing Masseter Surface Electromyography on EEG-Related Frequency Bands in Parkinson’s Disease Neuromotor Dysarthria

Speech has proven to be an effective neuromotor biomarker, capitalizing on the capabilities of contact-free technology. This study aims to evaluate the behavior of facial muscles’ activity estimating the entropy of their surface electromyographic (sEMG) activity during the production of diadochokinetic speech tests. The study explores the entropic behavior of the sEMG signal in certain frequency bands associated to EEG activity comparing participants affected by neuromotor diseases than in age-matched normative participants. Using recordings from two PD vs two HC participants on 5 EEG bands ( $$\delta , \vartheta , \alpha , \beta , \gamma $$ ), the maximum entropy estimated on the HC group was 5.70 10 $$^{-5}$$ , whereas the minimum entropy on the PD group was 7.25 10 $$^{-5}$$ . A hypothesis test rejected the similarity between the PD and HC results with a p-value under 0.0003. This different behavior might open the way to a wider study in characterizing neuromotor disease alterations from neuromotor origin.