A Neuromotor to Acoustical Jaw-Tongue Projection Model With Application in Parkinson's Disease Hypokinetic Dysarthria.

Autor:	Gómez A; Old Medical School, Medical School, Usher Institute, University of Edinburgh, Edinburgh, United Kingdom.; NeuSpeLab, Center for Biomedical Technology, Universidad Politécnica de Madrid, Madrid, Spain., Gómez P; NeuSpeLab, Center for Biomedical Technology, Universidad Politécnica de Madrid, Madrid, Spain., Palacios D; NeuSpeLab, Center for Biomedical Technology, Universidad Politécnica de Madrid, Madrid, Spain.; Escuela Técnica Superior de Ingeniería Informática-Universidad Rey Juan Carlos, Móstoles, Spain., Rodellar V; NeuSpeLab, Center for Biomedical Technology, Universidad Politécnica de Madrid, Madrid, Spain., Nieto V; NeuSpeLab, Center for Biomedical Technology, Universidad Politécnica de Madrid, Madrid, Spain., Álvarez A; NeuSpeLab, Center for Biomedical Technology, Universidad Politécnica de Madrid, Madrid, Spain., Tsanas A; Old Medical School, Medical School, Usher Institute, University of Edinburgh, Edinburgh, United Kingdom.
Jazyk:	angličtina
Zdroj:	Frontiers in human neuroscience [Front Hum Neurosci] 2021 Mar 15; Vol. 15, pp. 622825. Date of Electronic Publication: 2021 Mar 15 (Print Publication: 2021).
DOI:	10.3389/fnhum.2021.622825
Abstrakt:	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 information between sEMG and 3D acceleration, and acoustic features may be quantified using linear regression methods. Methods: Recordings from a cohort of eight age-matched control participants (4 males, 4 females) and eight PD participants (4 males, 4 females) were collected during the utterance of a diadochokinetic exercise (the fast repetition of diphthong [aI]). 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 absolute kinematic and acoustic velocities (AKV and AFV) 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 study also showed strong and significant cross-correlations between articulation kinematics, both for the control and the PD cohorts. The absolute kinematic variables presents an observable difference for the PD participants compared to the control group. Conclusion: Kinematic distributions derived from acoustic analysis may be useful biomarkers toward characterizing HD in neuromotor disorders providing new insights into PD. Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. (Copyright © 2021 Gómez, Gómez, Palacios, Rodellar, Nieto, Álvarez and Tsanas.)
Databáze:	MEDLINE
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