A identificação da fala interna por meio da eletromiografia de superfície e da encefalografia: uma revisão de escopo / The Identification of Internal Speech Through Surface Electromyography and Encephalography: a Scope Review

Kyvia Fernanda Tenório da Silva, Susana Carvalho, Miguel José Alves de Oliveira Júnior

Abstract


Resumo: O objetivo deste artigo é apresentar uma revisão de escopo sobre a identificação da fala interna por meio da eletromiografia de superfície e da encefalografia. Foi realizada uma busca na literatura dos últimos cinco anos (2015 a 2020), utilizando-se descritores em inglês e português, organizados de acordo com a seguinte sintaxe: (“silent speechORinner speechORcovert speechORself-talk” OR “imaginary speech”) AND (electromyography OR electromyographies OR “surface electromyography” “electromyographies, surface” OR “electromyography, surface” OR “surface electromyographies” OR electromyogram OR electromyograms OR electroencephalography OR EEG OR electroencephalogram OR electroencephalograms), sem incluir citações e patentes em diferentes bases de dados. A conceituação de fala interna diferiu entre os estudos incluídos nesta revisão, mas teve similaridade quanto à ausência de som e movimento articulatório. O propósito das pesquisas que analisaram os biossinais da eletroencefalografia e/ou eletromiografia de superfície na fala interna comparando-os ou não com a fala audível era desenvolver sistemas que sejam controlados pelo processamento mental da língua.

Palavras-chave: eletroencefalografia; eletromiografia; fala interna.

Abstract: The aim of this article is to present a scope review on the identification of internal speech through surface electromyography and encephalography. A search was performed in the literature of the last five years (2015 to 2020), using descriptors in English and Portuguese, organized according to the following syntax: (“silent speech” OR “inner speech” OR “covert speech” OR “self-talk” OR “imaginary speech”) AND (electromyography OR electromyographies OR “surface electromyography” “electromyographies, surface” OR “electromyography, surface” OR “surface electromyographies” OR electromyogram OR electromyograms OR electroencephalography OR EEG OR electroencephalogram OR electroencephalograms), not including citations and patents in different databases. The concept of internal speech differed among the studies included in this review, but it was similar in terms of the absence of sound and articulatory movement. The purpose of the research that analyzed the biosignals of electroencephalography and/or surface electromyography in internal speech, comparing them or not with audible speech, was to develop systems that are controlled by the mental processing of the language.

Keywords: surface electromyography; electroencephalography; inner speech.


Keywords


eletroencefalografia; eletromiografia; fala interna; surface electromyography; electroencephalography; inner speech.

References


BEHLAU, Mara; AZEVEDO, Renata; MADAZIO, Glaucya. Anatomia da Laringe e Fisiologia da Produção da Vocal. In: BEHLAU, M et al. Voz: o livro do especialista. vol. 1. 3⁰ ed., Rio de Janeiro: Livraria e Editora Revinter, 2013.

BOWERS, Andrew et al. Power and phase coherence in sensorimotor mu and temporal lobe alpha components during covert and overt syllable production. Experimental Brain Research. v. 237, p. 705–721, 2019.

BRADLEY, Jack N. et al. Inner speech is accompanied by a temporally-precise and content-specific corollary discharge. NeuroImage, v. 198, p. 170-180, 2019.

CHOMSKY, N. Novos Horizontes no Estudo da Linguagem. DELTA:

Documentação de Estudos em Lingüística Teórica e Aplicada [online].

, v. 13, n. spe, p. 51-74. DOI: https://doi.org/10.1590/S0102-

Disponível em:

>. Acesso em: 18 agosto 2021.

CHUYSUD, Kessarabhorn; PUNSAWAD, Yunyong. Hybrid EEG-fEMG based Human-Machine Interface for Communication and Control Applications. 16th International Joint Conference on Computer Science and Software Engineering (JCSSE), p. 1-5, 2019. DOI: 10.1109/JCSSE.2019.8864195

DENBY, Bruce. et al. Silent speech interfaces. Speech Communication, v. 52, n. 4, p. 270-287, 2010. DOI: https://doi.org/10.1016/j.specom.2009.08.002

GALEGO, Juliet S. Aquisição e processamento de biossinais de eletromiografia de superficie e eletroencefalografia para caracterização de commandos verbais ou intenção de fala mediante seu processamento matemático em pacientes com disartria. 2016. 159p. Dissertação. Programa de Pós-Graduação em Engenharia Elétrica, da Universidade Federal do Rio Grande do Sul, Porto Alegre, 2016.

JAHANGIRI, Amir; SEPULVEDA, Francisco. The contribution of different frequency bands in class separability of covert speech tasks for BCIs. IEEE. p. 2093-2096, 2017. DOI: 10.1109/EMBC.2017.8037266

JAHANGIRI, Amir et al. Covert Speech vs. Motor Imagery: a comparative study of class separability in identical environments. IEEE. p. 2020-2023, 2018. DOI: 10.1109/EMBC.2018.8512724

JAHANGIRI, Amir; ACHANCCARAY, David; SEPULVEDA, Francisco. A Novel EEG-Based Four-Class Linguistic BCI. IEEE. p. 3050-3053, 2019. DOI:

1109/EMBC.2019.8856644

JAHANGIRI, Amir.; SEPULVEDA, Francisco. The Relative Contribution of High-Gamma Linguistic Processing Stages of Word Production, and Motor Imagery of Articulation in Class Separability of Covert Speech Tasks in EEG Data. Journal of Medical Systems. v. 43, n. 20, 2019. Disponível em: https://link.springer.com/article/10.1007/s10916-018-1137-9. Acesso em: 17 de mai. 2021.

JANKE, Matthias; DIENER, Lorrenz. EMG-to-Speech: Direct Generation of Speech From Facial Electromyographic Signals. IEEE/ACM Transactions on Audio, Speech, and Language Processing. v. 25, p. 2375-2385, 2017. DOI: https://doi.org/10.1109/TASLP.2017.2738568

KENT, Ray D. Nonspeech Oral Movements and Oral Motor Disorders: A Narrative Review. Am J Speech Lang Pathol. n. 24, v. 4, p. 763-89, 2015. Disponível em: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4698470/#A1. Acesso em: 25 ago. 2021.

KOIZUMI, Koji; UEDA, Kazutaka; NAKAO, Masayuki. Development of a Cognitive Brain-Machine Interface Based on a Visual Imagery Method. IEEE, 2018, p. 1062-1065. 2018, DOI: 10.1109/EMBC.2018.8512520

KOMEILIPOOR, N.; CESARI, P.; DAFFERTSHOFER. A. Involvement of superior temporal areas in audiovisual and audiomotor speech integration. Neuroscience, v. 343, p. 276-283, 2017. DOI: 10.1016/j.

neuroscience.2016.03.047

NALBORCZYK, Ladislas et al. Can we decode phonetic features in inner speech using surface electromyography? Journal PLoS ONE, v. 5 p. 1-27, 2020. Disponível em: https://journals.plos.org/plosone/article/authors?id=10.1371/journal.pone.0233282. Acesso em: 05 de jun. 2021.

NALBORCZYK, Ladislas et al. Orofacial electromyographic correlates of induced verbal rumination. Biological psychology. vol. 127, p. 53-63, 2017. DOI: https://doi.org/10.1016/j.biopsycho.2017.04.013

NICOLAS-ALONSO, Luis F.; GOMEZ-GIL, Jaime. Brain computer interfaces, a review. Sensores Basel. v. 12, n. 2, p. 1211-1279, 2012. Disponível em: https://www.mdpi.com/1424-8220/12/2/1211/htm. Acesso em: 11 de jun. 2021.

NGUYEN, Choung. H.; KARAVAS, George K.; ARTEMIADIS, Panagiotis. Inferring imagined speech using EEG signals: a new approach using Riemannian Manifold features. Journal of Neural Engineering, v.15, n. 016002, p. 11-14, 2018. DOI: 10.1088/1741-2552/aa8235

PAWAR, Dipti.; DHAGE, Sudhir. Multiclass covert speech classification using extreme learning machine. Biomed. Eng. Lett. v. 10, p. 217–226, 2020. Disponível em: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7235109/. Acesso em: 31 de maio 2021.

RASO, T. Fala e escrita: meio, canal, consequências pragmáticas e

linguísticas. Domínios de Lingu@gem, Uberlândia, [S. l.], v. 7, n.

, p. 12–46, 2013. Disponível em:

dominiosdelinguagem/article/view/23730>. Acesso em: 19 jan. 2022.

SAUSSURE, F. Curso de linguística geral. Organização de Charles Bally

e Albert Sechehaye com a colaboração de Albert Riedlinger. Trad. de

Antônio Chelini, José Paulo Paes e Izidoro Blikstein. 27a ed. São Paulo:

Pensamento-Cultrix, 2006.

SRISUWAN, Niyawadee; PHUKPATTARANONT, Pornchai; LIMSAKUL, Chusak. Comparison of feature evaluation criteria for speech recognition based on electromyography. Med Biol Eng Comput. v. 56, n.6, p.1041-1051, 2018. DOI: 10.1007/s11517-017-1723-x

SERESHKEH, A. R. et al. Online EEG Classification of Covert Speech

for Brain-Computer Interfacing. International Journal of Neural Systems,

Cingapura, vol. 27, n. 8, 1750033, 2017. DOI: https://doi.org/10.1142/

S0129065717500332. Disponível em: https://www.worldscientific.

com/doi/10.1142/S0129065717500332?url_ver=Z39.88-2003&rfr_

id=ori:rid:crossref.org&rfr_dat=cr_pub%20%200pubmed. Acesso em:

de abr. 2021.

SCHULTZ, Tanja et al. Biosignal-Based Spoken Communication: A Survey. IEEE/ACM Trans. Audio, Speech and Lang. Proc. v. 25, n. 12, p. 2257–2271, 2017. DOI: 10.1109/TASLP.2017.2752365

STEPHAN, Franziska; SAALBACH, Henrik.; ROSSI, Sonja. Inner versus Overt Speech Production: Does This Make a Difference in the Developing Brain? Brain Sciences, v. 10, n. 12, 939, 2020. DOI: 10.3390/brainsci10120939

SILVA, T. C. et al. Fonética Acústica: os sons do português brasileiro.

TØTTRUP, L. et al. Decoding covert speech for intuitive control of brain-computer interfaces based on single-trial EEG: a feasibility study. IEEE, p. 689-693, 2019. DOI: 10.1109/ICORR.2019.8779499

TRICCO, Andrea C. et al. PRISMA Extension for Scoping Reviews (PRISMAScR): Checklist and Explanation. Annals of Internal Medicine. v.169, p. 467–473, 2018. doi: 10.7326/M18-0850. Disponível em: https://www.acpjournals.org/doi/full/10.7326/M18-0850?rfr_dat=cr_pub++0pubmed&url_ver=Z39.88-2003&rfr_id=ori%3Arid%3Acrossref.org. Acesso em: 11 de out. 2021.

WHITFORD, Thomas J. et al. Neurophysiological evidence of efference copies to inner speech. eLife. v. 6, ed. 28197, p.1-23, 2017. Disponível em: https://elifesciences.org/articles/28197#s4. Acesso em: 23 de abr. 2021.

YOSHIMURA, Natsue et al. Decoding of Covert Vowel Articulation Using Electroencephalography Cortical Currents. Frontiers in Neuroscience. v.10, p.175, 2016. Disponível em: https://www.frontiersin.org/article/10.3389/fnins.2016.00175. Acesso em 13 abr. 2021.




DOI: http://dx.doi.org/10.17851/2237-2083.30.3.1314-1338

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