Complex temporal patterns of bruxism require multi-day observation to capture clinically meaningful patterns, with three days being the minimum viable EMG monitoring period for comprehensive bruxism assessment.
Key Findings
Results
Sleep grinding episodes showed a progressive day-to-day increase across measurement nights.
A linear temporal model was used to characterize sleep grinding patterns.
The model revealed a day-to-day increase indicating progressive elevation in grinding activity across measurement nights.
20 subjects used a portable EMG device for 72 hours of continuous recording.
This finding suggests that single-night recordings may underestimate sleep grinding activity.
Results
Sleep clenching episodes demonstrated both a day-to-day increase and a linear decline across sleep hours within each night.
A basic model was used to characterize sleep clenching patterns.
The model revealed a day-to-day increase in clenching episodes.
Within each night, sleep clenching showed a linear decline across sleep hours.
This indicates that clenching is more prevalent in the earlier portions of the sleep period.
Results
Awake grinding episodes showed an hourly decline throughout waking hours with no significant day-to-day variation.
A linear temporal model revealed a decline in grinding episodes across waking hours.
No significant day-to-day variation was observed for awake grinding.
This temporal pattern distinguishes awake grinding from sleep grinding, which showed day-to-day increases.
The finding suggests grinding activity diminishes as the waking day progresses.
Results
Awake clenching episodes exhibited curvilinear (polynomial) patterns for both hourly and daily variations.
A polynomial model best characterized awake clenching temporal patterns.
Curvilinear patterns were observed for both hourly variation within each day and daily variation across the monitoring period.
This nonlinear pattern is distinct from the linear patterns observed for other bruxism behaviors.
The complexity of awake clenching patterns requires polynomial rather than simple linear modeling.
Results
The four bruxism behavior types (sleep grinding, sleep clenching, awake grinding, awake clenching) displayed distinct temporal signatures from one another.
Sleep and awake bruxism showed different temporal dynamics, as did grinding versus clenching behaviors.
Sleep grinding followed a linear day-to-day increase; sleep clenching showed both a day-to-day increase and nightly decline.
Awake grinding showed a linear hourly decline; awake clenching showed curvilinear daily and hourly patterns.
These distinct temporal signatures 'support the need for differentiated monitoring protocols' for each behavior type.
Results
Three days was identified as the minimum viable EMG monitoring period for comprehensive bruxism assessment.
The study used 72 hours (3 days/nights) of continuous portable EMG recording in 20 subjects.
The authors concluded that 'three days might be the minimum viable EMG monitoring period for comprehensive bruxism assessment.'
Single-day assessments were characterized as potentially missing 'critical temporal dynamics' and underestimating 'the condition's severity and variability.'
The authors recommend standardization regarding EMG variables and minimum recording period for future studies.
Methods
The study employed a mixed model analysis framework to evaluate both hourly and day-to-day variations in bruxism episodes.
20 subjects participated, each wearing a portable EMG device for 72 continuous hours.
Variables analyzed included number of grinding and clenching episodes per hour of sleep and per hour of wakefulness.
Additional variables were supplied by the instrument's built-in algorithm.
Separate temporal models (linear vs. polynomial vs. basic) were selected for each of the four bruxism behavior types based on best fit.
What This Means
This research suggests that teeth grinding and clenching — collectively known as bruxism — follow complex and distinct patterns depending on whether they occur during sleep or while awake, and whether the behavior is grinding (back-and-forth jaw movement) versus clenching (sustained jaw pressure). Using small wearable muscle activity sensors worn continuously for three days and nights by 20 participants, researchers found that nighttime grinding tended to get worse each successive night, while nighttime clenching was highest early in the sleep period and tapered off. Daytime grinding, by contrast, was highest in the morning and decreased as the day went on, while daytime clenching followed a more complex wave-like pattern both within each day and across the three days.
A particularly important practical implication is that recording bruxism for only a single day or night may paint a misleading picture. Because each type of bruxism behavior follows its own unique time course that unfolds over multiple days, a snapshot from just one recording session could miss the true severity or variability of the problem. The researchers suggest that three days is likely the minimum monitoring period needed to get a clinically useful picture of a person's bruxism.
This research also highlights that sleep bruxism and awake bruxism should not be treated as a single condition when it comes to measurement and monitoring. Their different temporal patterns suggest they may have different underlying mechanisms and may need to be tracked separately. The authors call for standardization in how bruxism is measured using portable devices — including which specific measurements are used and how long recordings should last — so that future research and clinical assessments can be more consistent and comparable.
Alona E, Amit S, Khalil M, Ilana E. (2026). Temporal patterns of bruxism behaviors: multiple day recording with portable electromyography.. Scientific reports. https://doi.org/10.1038/s41598-025-30704-z