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

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Artificial Intelligence in Neuroscience: Affective Analysis and Health Applications (IWINAC 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13258))

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Abstract

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.

This research received funding from grants TEC2016-77791-C4-4-R (Ministry of Economic Affairs and Competitiveness of Spain), and Teca-Park-MonParLoc FGCSIC-CENIE 0348-CIE-6-E (InterReg Programme). The authors wish to thank Víctor Lorente for his inspiring thoughts (School of Veterinary, UCM, Spain).

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Author information

Authors and Affiliations

  1. Faculty of Medicine, Usher Institute, University of Edinburgh, Edinburgh, UK

    Andrés Gómez-Rodellar & Athanasios Tsanas

  2. NeuSpeLab, CTB, Universidad Politécnica de Madrid, 28220, Pozuelo de Alarcón, Madrid, Spain

    Pedro Gómez-Vilda

  3. Universidad Politécnica de Cartagena, Campus Muralla del Mar, Pza. Hospital 1, 30202, Cartagena, Spain

    JoséManuel Ferrández-Vicente

Authors
  1. Andrés Gómez-Rodellar
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  2. Pedro Gómez-Vilda
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  3. JoséManuel Ferrández-Vicente
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  4. Athanasios Tsanas
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Corresponding author

Correspondence to Pedro Gómez-Vilda .

Editor information

Editors and Affiliations

  1. Universidad Politécnica de Cartagena, Cartagena, Spain

    José Manuel Ferrández Vicente

  2. Universidad Nacional de Educación a Distancia, Madrid, Spain

    José Ramón Álvarez-Sánchez

  3. Universidad Nacional de Educación a Distancia, Madrid, Spain

    Félix de la Paz López

  4. Ohio State University, Columbus, OH, USA

    Hojjat Adeli

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Gómez-Rodellar, A., Gómez-Vilda, P., Ferrández-Vicente, J., Tsanas, A. (2022). Characterizing Masseter Surface Electromyography on EEG-Related Frequency Bands in Parkinson’s Disease Neuromotor Dysarthria. In: Ferrández Vicente, J.M., Álvarez-Sánchez, J.R., de la Paz López, F., Adeli, H. (eds) Artificial Intelligence in Neuroscience: Affective Analysis and Health Applications. IWINAC 2022. Lecture Notes in Computer Science, vol 13258. Springer, Cham. https://doi.org/10.1007/978-3-031-06242-1_22

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  • DOI: https://doi.org/10.1007/978-3-031-06242-1_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-06241-4

  • Online ISBN: 978-3-031-06242-1

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