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.