Electromyographic Patterns and the Identification of Subtypes of Awake Bruxism

Abstract

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.