Year: 2015
Type: article
Abstract: Study Objectives: Assessment of jaw-muscle activity during sleep is needed to establish a definite diagnosis of sleep bruxism (SB).Multichannel polysomnographic (PSG) studies are the gold standard (GS) but are unfortunately not readily available, so singlechannel electromyographic (EMG) devices have been developed.This study attempted to evaluate an EMG algorithm for singlechannel EMG recordings in comparison with the outcome from PSG recordings.Methods: PSG data from 20 participants with different frequency of jaw-muscle EMG activity were analyzed with the GS algorithm, including previously published criteria for EMG analyses and contrasted to two different algorithms: one based on a signal recognition (SR) algorithm and the other based on a moving average (MA) estimation method, which is characterized by a comparison of the EMG amplitude to the estimated background level, and applying the rules for detection of rhythmic masticatory muscle activity (RMMA).Results: The highest correlation coefficients (r = 0.96) were obtained between the GS and the MA algorithm; however, there were no significant differences in the absolute numbers of EMG bursts or episodes between the SR and MA algorithms and GS during sleep.However, both algorithms significantly overestimated the EMG bursts and episodes when awakenings during sleep were included in the analyses.There were no significant differences between muscles or side (p > 0.06). Conclusions:This study strongly indicates that a MA algorithm may be useful for analysis of EMG activity during sleep but with recognition of the potential overestimation of EMG bursts and episodes due to transient awakenings.
Source: Journal of Dental Sleep Medicine
DOI: 10.15331/jdsm.5112
Author: Leslie C. Dort
Language: English
Subfield: Oral Surgery
Field: Dentistry
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W2802669019