A Neuromotor to Acoustical Jaw-Tongue Projection Model With Application in Parkinson’s Disease Hypokinetic Dysarthria - Gómez, Andrés; Gómez, Pedro; Palacios, Daniel; Rodellar, Victoria; Nieto, Víctor; Álvarez, Agustín; Tsanas, Athanasios (Frontiers in Human Neuroscience, 2021)
Aim: The present work proposes the study of the neuromotor activity of the masseter-jaw-tongue articulation during diadochokinetic exercising to establish functional statistical relationships between surface Electromyography (sEMG), 3D Accelerometry (3DAcc), and acoustic features extracted from the speech signal, with the aim of characterizing Hypokinetic Dysarthria (HD). A database of multi-trait signals of recordings from an age-matched control and PD participants are used in the experimental study. Hypothesis: The main assumption is that strong cross-correlations between sEMG and 3D acceleration, and acoustic features may be assessed by linear regression methods. Methods: A subset of six age-matched control participants (3 males, 3 females) and six PD participants (3 males, 3 females) were recorded during the utterance of a diadochokinetic exercise. The dynamic and acoustic absolute kinematic velocities produced during the exercises were estimated by acoustic filter inversion and numerical integration and differentiation of the speech signal. The amplitude distributions of the kinematic velocities (Kinematic Distributions) are estimated to allow comparisons in terms of Mutual Information. Results: The regression results show the relationships between sEMG and dynamic and acoustic estimates. The projection methodology may help in understanding the basic neuromotor muscle activity regarding neurodegenerative speech in remote monitoring neuromotor and neurocognitive diseases using speech as the vehicular tool, and in the study of other speech-related disorders. The regression study showed strong and significant cross-correlations between articulation kinematics, both for the control and the PD participants. The absolute kinematic variables presents an observable difference for the PD participants compared to the controls. Conclusions: Kinematic distributions derived from acoustic analysis may be useful biomarkers of HD in neuromotor disorders applying Mutual Information methodologies.