Electromyographic Patterns and the Identification of Subtypes of Awake Bruxism

Electromyographic Patterns and the Identification of Subtypes of Awake Bruxism

The future of awake bruxism assessment will incorporate physiological data, possibly electromyography (EMG) of the temporal muscles. But up to now, temporal muscle contraction patterns in awake bruxism have not been characterized to demonstrate clinical utility. The present study aimed to perform su...

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Published in:Frontiers in human neuroscience Vol. 14; p. 601881
Main Authors: Monteiro, Ubirakitan Maciel, Soares, Vinicius Belém Rodrigues Barros, Soares, Caio Belém Rodrigues Barros, Pinto, Tiago Coimbra Costa, Ximenes, Rosana Christine Cavalcanti, Araújo Cairrão Rodrigues, Marcelo
Format: Journal Article
Language:English
Published: Switzerland Frontiers Research Foundation 28-01-2021
Frontiers Media S.A
Subjects:
awake bruxism
Calibration
Cluster analysis
Dentists
Electrodes
Electromyography
Human Neuroscience
Muscle contraction
Muscle function
Pain
phasic contractions
Physiology
Signal processing
Software
Statistical analysis
Teeth
temporal muscle
tonic contraction
Brazil
temporal muscle
awake bruxism
phasic contractions
cluster analysis
tonic contraction
electromyography
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Summary:The future of awake bruxism assessment will incorporate physiological data, possibly electromyography (EMG) of the temporal muscles. But up to now, temporal muscle contraction patterns in awake bruxism have not been characterized to demonstrate clinical utility. The present study aimed to perform surface EMG evaluations of people assessed for awake bruxism to identify possible different subtypes. A 2-year active search for people with awake bruxism in three regions of the country resulted in a total of 303 participants (223 women, 38 ± 13 years, mean and SD). Their inclusion was confirmed through non-instrumental approaches for awake bruxism: self-reported questionnaire and clinical exam, performed by three experienced and calibrated dentists (Kappa = 0.75). Also, 77 age- and sex-matched healthy controls were recruited (49 women, 36 ± 14 years). Temporalis surface EMG was performed with a portable device (Myobox; NeuroUp, Brazil). EMG signals were sent to a computer via Bluetooth 4.0 at a sampling rate of 1,000 Hz. Digital signal processing was performed using the commercial neuroUP software, transformed in RMS and then normalized for peak detection (EMG peaks/min), in a 10 min session. Cluster analysis revealed three distinct subtypes of awake bruxism: phasic, tonic, and intermediate. Individuals with a predominance of EMG peaks/min were classified as the "phasic" subtype (16.8%). Those with the highest EMG rest power were classified as the "tonic" subtype (32.3%). There was also an "intermediate" subtype (50.8%), when both variables remained low. Characterization of awake bruxism physiology is important for future establishment of instrumental assessment protocols and treatment strategies.
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Reviewed by: Riccardo Rosati, University of Milan, Italy; Jari Ahlberg, University of Helsinki, Finland
This article was submitted to Motor Neuroscience, a section of the journal Frontiers in Human Neuroscience
Edited by: Teresa Lever, University of Missouri, United States
ISSN:1662-5161
1662-5161
DOI:10.3389/fnhum.2020.601881