Automated assessment of rhythmic masticatory muscle activity

Objectives: Rhythmic masticatory muscle activity (RMMA) occurring in sleep bruxers is generally scored by means of polysomnography (PSG). A major disadvantage of this equipment is the high cost and long time needed for manual/visual scoring. Aim of this study was to test a new method for automated scoring of RMMA using one-channel EMG recordings, and to determine its agreement to PSG scoring.

Methods: Complete one-night PSG recordings were obtained from 10 sleep bruxers (5 men, 5 women; age=28.2±5.8 years). RMMA was scored using the whole PSG recordings by one experienced examiner under independent conditions. Thereafter, RMMA was scored automatically by means of a specially developed algorithm applied to a one-channel electromyographic (EMG) recording from the masseter muscle. The algorithm base-band Demodulated the EMG signal providing a Frequency vs. Time representation (DEFT) and had been previously validated using well-defined controlled rhythmic oral activities. The proportion of correctly classified RMMA episodes and of discordant detections was used to quantify agreement between PSG and DEFT.

Results: Using PSG it was found that the number of RMMA episodes per hour of sleep was 6.5 ± 2.7, whereas 7.2 ± 2.8 were found by DEFT, the difference being non significant (t-test: p=0.12). The proportion of RMMA episodes found by PSG concordantly identified by DEFT was 72.2% ± 8.2 (range: 60.0% to 85.1%). The proportion of episodes found by DEFT and concordantly identified by PSG was 70.7% (range: 55.0% to 95.4%). Total duration of RMMA assessed by DEFT was about 30% shorter than that assessed by PSG.

Conclusions: Despite the need for further clarification of inconsistencies between PSG and DEFT, the proposed method represents a promising tool to effectively investigate rhythmical contractions of the masticatory muscles using one-channel EMG recordings.