Electrophysiological predictors of hyperfunctional dysphonia.

Dysphonia blood volume pulse signal electrophysiology heart rate variability voice

Journal

Acta oto-laryngologica
ISSN: 1651-2251
Titre abrégé: Acta Otolaryngol
Pays: England
ID NLM: 0370354

Informations de publication

Date de publication:
Jan 2023
Historique:
pubmed: 4 1 2023
medline: 9 2 2023
entrez: 3 1 2023
Statut: ppublish

Résumé

The relation between the autonomic nervous system (ANS) and muscles of the vocal tract is of particular importance when considering the pathomechanism of a functional voice disorder. The aim of this study was to record electrophysiological indicators from the ANS as well as the tone of the external laryngeal muscle and test whether together they could point to an enhanced risk of primary functional voice disorder. The study material consisted of 81 people, 27 of whom were professional opera singers. None reported any voice complaints. The research comprised ENT and phoniatric examination, superficial electromyography (SEMG), and recording of physiological indicators (pulse rate, skin resistance). All subjects had a clear voice with no sign of vocal disability. Endoscopy revealed laryngeal hyperfunction in 26 people. SEMG revealed that the 26 had increased external laryngeal muscle tone during phonation, and this finding correlated with a change in certain electrophysiological indicators HRV, BVP, EDA. We conclude that anomalies in electrophysiological parameters in individuals with subclinical symptoms of functional voice disorder may be at risk of developing fully symptomatic hyperfunctional dysphonia in the future. Vocal training, which differentiates singers and non-singers, is known to have an effect on subclinical hyperfunctional dysphonia. By measuring indicators of hyperfunctional dysphonia, it may be possible to take remedial action before symptomatic dysphonia develops.

Sections du résumé

BACKGROUND UNASSIGNED
The relation between the autonomic nervous system (ANS) and muscles of the vocal tract is of particular importance when considering the pathomechanism of a functional voice disorder.
AIMS UNASSIGNED
The aim of this study was to record electrophysiological indicators from the ANS as well as the tone of the external laryngeal muscle and test whether together they could point to an enhanced risk of primary functional voice disorder.
MATERIALS AND METHODS UNASSIGNED
The study material consisted of 81 people, 27 of whom were professional opera singers. None reported any voice complaints. The research comprised ENT and phoniatric examination, superficial electromyography (SEMG), and recording of physiological indicators (pulse rate, skin resistance).
RESULTS UNASSIGNED
All subjects had a clear voice with no sign of vocal disability. Endoscopy revealed laryngeal hyperfunction in 26 people. SEMG revealed that the 26 had increased external laryngeal muscle tone during phonation, and this finding correlated with a change in certain electrophysiological indicators HRV, BVP, EDA.
CONCLUSIONS UNASSIGNED
We conclude that anomalies in electrophysiological parameters in individuals with subclinical symptoms of functional voice disorder may be at risk of developing fully symptomatic hyperfunctional dysphonia in the future. Vocal training, which differentiates singers and non-singers, is known to have an effect on subclinical hyperfunctional dysphonia.
SIGNIFICANCE UNASSIGNED
By measuring indicators of hyperfunctional dysphonia, it may be possible to take remedial action before symptomatic dysphonia develops.

Identifiants

pubmed: 36595463
doi: 10.1080/00016489.2022.2162961
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

56-63

Auteurs

Agata Szkiełkowska (A)

Audiology and Phoniatrics Clinic, Institute of Physiology and Pathology of Hearing, Warsaw, Poland.

Paulina Krasnodębska (P)

Audiology and Phoniatrics Clinic, Institute of Physiology and Pathology of Hearing, Warsaw, Poland.

Andrzej Mitas (A)

Department of Medical Informatics and Artificial Intelligence, Faculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland.

Monika Bugdol (M)

Department of Medical Informatics and Artificial Intelligence, Faculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland.

Marcin Bugdol (M)

Department of Medical Informatics and Artificial Intelligence, Faculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland.

Patrycja Romaniszyn-Kania (P)

Department of Medical Informatics and Artificial Intelligence, Faculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland.

Anita Pollak (A)

University of Silesia, Institute of Psychology, Katowice, Poland.

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Classifications MeSH