website: 86th General Session & Exhibition of the IADR

ABSTRACT: 2749  

Comparison of Ambulatory and Sleep Laboratory Oromotor Recordings in Normals

T. YAMAGUCHI1, S. ABE2, H.E. ALAOUI2, and G.J. LAVIGNE2, 1Hokkaido University, Sappro, Japan, 2Université de Montréal, Canada

Objectives: Reliable and simple EMG Sleep Bruxism (SB) recording systems are needed for clinical and longitudinal studies. The aim of this study is to compare a newly developed ambulatory electromyogram (EMG) recorder named BMS with sleep-laboratory based polysomnograph (PSG) audio and video recordings.

Methods: The BMS is a telemetric device that consists of ultraminiature transmitter units with built-in bipolar electrodes and a receiver unit. Eight volunteer subjects without an obvious current history of tooth grinding spent one night in a sleep laboratory. Simultaneous EMG recordings were made with a BMS attached to one masseter muscle and PSG electrode to the opposite masseter. Independent scoring of the BMS signal was carried out only on masseteric EMG. Scoring of oromotor activity was done according to published criteria (Lavigne, J Dent Res, 1996; 2001). Both scoring types were compared. Sensitivity and positive predictive value of BMS concerning oromotor episodes were calculated using PSG data as the standard. Correlation was estimated between EMG scorings of BMS and PSG.

Results: 1) A mean of 51.6 oromotor episodes was detected with the BMS in comparison to 25.5 with PSG. 2) BMS sensitivity was 82.8% and positive predictive value was 40.9%. Due to the absence of sleep stage scoring, BMS scorings included 79.5% of false positive signals in wake stage. 3) Correlation between BMS and PSG oromotor episodes detection was positive and significant (r =0.935, P<0.05).

Conclusions: The BMS was fairly sensitive at detecting oromotor episodes. However, detection only based on masseteric EMG activity tends to cause excessive false positives due to lack of wake stage recognition. To further reduce BMS false positive scoring, use of another device that estimates wake stage may be helpful. The development of an algorithm to discriminate between BMS and PSG is also considered.

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