Neuromechanical Modelling of Articulatory Movements from Surface Electromyography and Speech Formants
Speech articulation is produced by the movements of muscles in the larynx, pharynx, mouth and face. Therefore speech shows acoustic features as formants which are directly related with neuromotor actions of these muscles. The first two formants are strongly related with jaw and tongue muscular activ...
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Veröffentlicht in: | International journal of neural systems 2019-03, Vol.29 (2), p.1850039 |
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creator | Gómez-Vilda, Pedro Gómez-Rodellar, Andrés Vicente, José M. Ferrández Mekyska, Jiri Palacios-Alonso, Daniel Rodellar-Biarge, Victoria Álvarez-Marquina, Agustín Eliasova, Ilona Kostalova, Milena Rektorova, Irena |
description | Speech articulation is produced by the movements of muscles in the larynx, pharynx, mouth and face. Therefore speech shows acoustic features as formants which are directly related with neuromotor actions of these muscles. The first two formants are strongly related with jaw and tongue muscular activity. Speech can be used as a simple and ubiquitous signal, easy to record and process, either locally or on e-Health platforms. This fact may open a wide set of applications in the study of functional grading and monitoring neurodegenerative diseases. A relevant question, in this sense, is how far speech correlates and neuromotor actions are related. This preliminary study is intended to find answers to this question by using surface electromyographic recordings on the masseter and the acoustic kinematics related with the first formant. It is shown in the study that relevant correlations can be found among the surface electromyographic activity (dynamic muscle behavior) and the positions and first derivatives of the first formant (kinematic variables related to vertical velocity and acceleration of the joint jaw and tongue biomechanical system). As an application example, it is shown that the probability density function associated to these kinematic variables is more sensitive than classical features as Vowel Space Area (VSA) or Formant Centralization Ratio (FCR) in characterizing neuromotor degeneration in Parkinson’s Disease. |
doi_str_mv | 10.1142/S0129065718500399 |
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Ferrández ; Mekyska, Jiri ; Palacios-Alonso, Daniel ; Rodellar-Biarge, Victoria ; Álvarez-Marquina, Agustín ; Eliasova, Ilona ; Kostalova, Milena ; Rektorova, Irena</creator><creatorcontrib>Gómez-Vilda, Pedro ; Gómez-Rodellar, Andrés ; Vicente, José M. Ferrández ; Mekyska, Jiri ; Palacios-Alonso, Daniel ; Rodellar-Biarge, Victoria ; Álvarez-Marquina, Agustín ; Eliasova, Ilona ; Kostalova, Milena ; Rektorova, Irena</creatorcontrib><description>Speech articulation is produced by the movements of muscles in the larynx, pharynx, mouth and face. Therefore speech shows acoustic features as formants which are directly related with neuromotor actions of these muscles. The first two formants are strongly related with jaw and tongue muscular activity. Speech can be used as a simple and ubiquitous signal, easy to record and process, either locally or on e-Health platforms. This fact may open a wide set of applications in the study of functional grading and monitoring neurodegenerative diseases. A relevant question, in this sense, is how far speech correlates and neuromotor actions are related. This preliminary study is intended to find answers to this question by using surface electromyographic recordings on the masseter and the acoustic kinematics related with the first formant. It is shown in the study that relevant correlations can be found among the surface electromyographic activity (dynamic muscle behavior) and the positions and first derivatives of the first formant (kinematic variables related to vertical velocity and acceleration of the joint jaw and tongue biomechanical system). As an application example, it is shown that the probability density function associated to these kinematic variables is more sensitive than classical features as Vowel Space Area (VSA) or Formant Centralization Ratio (FCR) in characterizing neuromotor degeneration in Parkinson’s Disease.</description><identifier>ISSN: 0129-0657</identifier><identifier>EISSN: 1793-6462</identifier><identifier>DOI: 10.1142/S0129065718500399</identifier><identifier>PMID: 30409059</identifier><language>eng</language><publisher>Singapore: World Scientific Publishing Company</publisher><subject>Biomechanics ; Correlation analysis ; Degeneration ; Electromyography ; Kinematics ; Larynx ; Muscles ; Neurological diseases ; Pharynx ; Probability density functions ; Research Article ; Signal processing ; Speech ; Tongue</subject><ispartof>International journal of neural systems, 2019-03, Vol.29 (2), p.1850039</ispartof><rights>2019, The Author(s)</rights><rights>2019. The Author(s). This is an Open Access article published by World Scientific Publishing Company. It is distributed under the terms of the Creative Commons Attribution 4.0 (CC-BY) License. Further distribution of this work is permitted, provided the original work is properly cited.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4139-4ee6a45fa00dfe5f78ce76de1ea732c14c7b80b09da42fd091fa706b601f7ce83</citedby><cites>FETCH-LOGICAL-c4139-4ee6a45fa00dfe5f78ce76de1ea732c14c7b80b09da42fd091fa706b601f7ce83</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.worldscientific.com/doi/reader/10.1142/S0129065718500399$$EPDF$$P50$$Gworldscientific$$Hfree_for_read</linktopdf><link.rule.ids>314,776,780,27476,27903,27904,55547</link.rule.ids><linktorsrc>$$Uhttp://dx.doi.org/10.1142/S0129065718500399$$EView_record_in_World_Scientific_Publishing$$FView_record_in_$$GWorld_Scientific_Publishing$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30409059$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Gómez-Vilda, Pedro</creatorcontrib><creatorcontrib>Gómez-Rodellar, Andrés</creatorcontrib><creatorcontrib>Vicente, José M. Ferrández</creatorcontrib><creatorcontrib>Mekyska, Jiri</creatorcontrib><creatorcontrib>Palacios-Alonso, Daniel</creatorcontrib><creatorcontrib>Rodellar-Biarge, Victoria</creatorcontrib><creatorcontrib>Álvarez-Marquina, Agustín</creatorcontrib><creatorcontrib>Eliasova, Ilona</creatorcontrib><creatorcontrib>Kostalova, Milena</creatorcontrib><creatorcontrib>Rektorova, Irena</creatorcontrib><title>Neuromechanical Modelling of Articulatory Movements from Surface Electromyography and Speech Formants</title><title>International journal of neural systems</title><addtitle>Int J Neural Syst</addtitle><description>Speech articulation is produced by the movements of muscles in the larynx, pharynx, mouth and face. Therefore speech shows acoustic features as formants which are directly related with neuromotor actions of these muscles. The first two formants are strongly related with jaw and tongue muscular activity. Speech can be used as a simple and ubiquitous signal, easy to record and process, either locally or on e-Health platforms. This fact may open a wide set of applications in the study of functional grading and monitoring neurodegenerative diseases. A relevant question, in this sense, is how far speech correlates and neuromotor actions are related. This preliminary study is intended to find answers to this question by using surface electromyographic recordings on the masseter and the acoustic kinematics related with the first formant. It is shown in the study that relevant correlations can be found among the surface electromyographic activity (dynamic muscle behavior) and the positions and first derivatives of the first formant (kinematic variables related to vertical velocity and acceleration of the joint jaw and tongue biomechanical system). As an application example, it is shown that the probability density function associated to these kinematic variables is more sensitive than classical features as Vowel Space Area (VSA) or Formant Centralization Ratio (FCR) in characterizing neuromotor degeneration in Parkinson’s Disease.</description><subject>Biomechanics</subject><subject>Correlation analysis</subject><subject>Degeneration</subject><subject>Electromyography</subject><subject>Kinematics</subject><subject>Larynx</subject><subject>Muscles</subject><subject>Neurological diseases</subject><subject>Pharynx</subject><subject>Probability density functions</subject><subject>Research Article</subject><subject>Signal processing</subject><subject>Speech</subject><subject>Tongue</subject><issn>0129-0657</issn><issn>1793-6462</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>ADCHV</sourceid><recordid>eNplkEFLwzAYhoMobk5_gBcJeK5-adOmOY6xqTD1MD2XNP2ydbTNTFul_96MzV08Bb73ed_AQ8gtgwfGePi4AhZKSGLB0hggkvKMjJmQUZDwJDwn430c7PMRuWrbLQDjgqeXZBQBBwmxHBN8w97ZGvVGNaVWFX21BVZV2aypNXTqulL3leqsG3zyjTU2XUuNb9BV74zSSOcV6s4fBrt2arcZqGoKutqhn6QL62rlG9fkwqiqxZvjOyGfi_nH7DlYvj-9zKbLQHMWyYAjJorHRgEUBmMjUo0iKZChElGoGdciTyEHWSgemgIkM0pAkifAjNCYRhNyf9jdOfvVY9tlW9u7xn-ZhSzlkoUi4p5iB0o727YOTbZzZa3ckDHI9mKzf2J95-643Oc1FqfGn0kPwAH4sa4qWl16U6Up9Yn8v_kL2e6Edw</recordid><startdate>201903</startdate><enddate>201903</enddate><creator>Gómez-Vilda, Pedro</creator><creator>Gómez-Rodellar, Andrés</creator><creator>Vicente, José M. Ferrández</creator><creator>Mekyska, Jiri</creator><creator>Palacios-Alonso, Daniel</creator><creator>Rodellar-Biarge, Victoria</creator><creator>Álvarez-Marquina, Agustín</creator><creator>Eliasova, Ilona</creator><creator>Kostalova, Milena</creator><creator>Rektorova, Irena</creator><general>World Scientific Publishing Company</general><general>World Scientific Publishing Co. Pte., Ltd</general><scope>ADCHV</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>201903</creationdate><title>Neuromechanical Modelling of Articulatory Movements from Surface Electromyography and Speech Formants</title><author>Gómez-Vilda, Pedro ; Gómez-Rodellar, Andrés ; Vicente, José M. Ferrández ; Mekyska, Jiri ; Palacios-Alonso, Daniel ; Rodellar-Biarge, Victoria ; Álvarez-Marquina, Agustín ; Eliasova, Ilona ; Kostalova, Milena ; Rektorova, Irena</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4139-4ee6a45fa00dfe5f78ce76de1ea732c14c7b80b09da42fd091fa706b601f7ce83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Biomechanics</topic><topic>Correlation analysis</topic><topic>Degeneration</topic><topic>Electromyography</topic><topic>Kinematics</topic><topic>Larynx</topic><topic>Muscles</topic><topic>Neurological diseases</topic><topic>Pharynx</topic><topic>Probability density functions</topic><topic>Research Article</topic><topic>Signal processing</topic><topic>Speech</topic><topic>Tongue</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gómez-Vilda, Pedro</creatorcontrib><creatorcontrib>Gómez-Rodellar, Andrés</creatorcontrib><creatorcontrib>Vicente, José M. 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Ferrández</au><au>Mekyska, Jiri</au><au>Palacios-Alonso, Daniel</au><au>Rodellar-Biarge, Victoria</au><au>Álvarez-Marquina, Agustín</au><au>Eliasova, Ilona</au><au>Kostalova, Milena</au><au>Rektorova, Irena</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Neuromechanical Modelling of Articulatory Movements from Surface Electromyography and Speech Formants</atitle><jtitle>International journal of neural systems</jtitle><addtitle>Int J Neural Syst</addtitle><date>2019-03</date><risdate>2019</risdate><volume>29</volume><issue>2</issue><spage>1850039</spage><pages>1850039-</pages><issn>0129-0657</issn><eissn>1793-6462</eissn><abstract>Speech articulation is produced by the movements of muscles in the larynx, pharynx, mouth and face. Therefore speech shows acoustic features as formants which are directly related with neuromotor actions of these muscles. The first two formants are strongly related with jaw and tongue muscular activity. Speech can be used as a simple and ubiquitous signal, easy to record and process, either locally or on e-Health platforms. This fact may open a wide set of applications in the study of functional grading and monitoring neurodegenerative diseases. A relevant question, in this sense, is how far speech correlates and neuromotor actions are related. This preliminary study is intended to find answers to this question by using surface electromyographic recordings on the masseter and the acoustic kinematics related with the first formant. It is shown in the study that relevant correlations can be found among the surface electromyographic activity (dynamic muscle behavior) and the positions and first derivatives of the first formant (kinematic variables related to vertical velocity and acceleration of the joint jaw and tongue biomechanical system). 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subjects | Biomechanics Correlation analysis Degeneration Electromyography Kinematics Larynx Muscles Neurological diseases Pharynx Probability density functions Research Article Signal processing Speech Tongue |
title | Neuromechanical Modelling of Articulatory Movements from Surface Electromyography and Speech Formants |
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