The Bruxoff Device as a Screening Method for Sleep Bruxism in Dental Practice

Advanced Sensing System for Sleep Bruxism across Multiple Postures via EMG and Machine Learning

Diagnosis of bruxism is challenging because not all contractions of the masticatory muscles can be classified as bruxism. Conventional methods for sleep bruxism detection vary in effectiveness. Some provide objective data through EMG, ECG, or EEG; others, such as dental implants, are less accessible for daily practice. These methods have targeted the masseter as the key muscle for bruxism detection. However, it is important to consider that the temporalis muscle is also active during bruxism among masticatory muscles. Moreover, studies have predominantly examined sleep bruxism in the supine position, but other anatomical positions are also associated with sleep. In this research, we have collected EMG data to detect the maximum voluntary contraction of the temporalis and masseter muscles in three primary anatomical positions associated with sleep, i.e., supine and left and right lateral recumbent positions. A total of 10 time domain features were extracted, and six machine learning classifiers were compared, with random forest outperforming others. The models achieved better accuracies in the detection of sleep bruxism with the temporalis muscle. An accuracy of 93.33% was specifically found for the left lateral recumbent position among the specified anatomical positions. These results indicate a promising direction of machine learning in clinical applications, facilitating enhanced diagnosis and management of sleep bruxism.

Relationship between Sleep Bruxism Determined by Non-Instrumental and Instrumental Approaches and Psychometric Variables

Sleep bruxism (SB) can be determined with different diagnostic procedures. The relationship between psychometric variables and SB varies depending on the diagnostic method. The aim of the study was to compare the association between SB and oral health-related quality of life (OHRQoL; measured by the Oral Health Impact Profile, OHIP), anxiety (measured by the State-Trait anxiety inventory, STAI), and stress (single scale variable) depending on the diagnostic method in the same sample. N = 45 participants were examined by non-instrumental (possible/probable SB) and instrumental methods (definite SB). The OHIP differed significantly between possible SB (median = 4) and non-SB (median = 0) with W = 115, p = 0.01, and probable SB (median = 6) and non-SB (median = 0) with W = 101, p = 0.01). There was no significant difference in the OHIP score between definite SB and non-SB. For the other psychometric variables, the analyses revealed no significant differences between SB and non-SB in all diagnostic procedures. The results suggest that there is a difference between possible/probable and definite SB with respect to the association with OHRQoL. Certain aspects of possible/probable SB might be responsible for the poor OHRQoL, which are not measured in definite SB.

Cannabidiol Intervention for Muscular Tension, Pain, and Sleep Bruxism Intensity-A Randomized, Double-Blind Clinical Trial

Background: Temporomandibular disorders (TMDs) are the most prevalent non-dental pain issues in the maxillofacial region. Despite advancements, diagnosing and managing TMDs continues to pose challenges. This study aimed to assess the efficacy of cannabidiol (CBD) formulations, with different concentrations, in patients experiencing sleep bruxism and muscle-related TMDs, with a particular emphasis on their myorelaxant, pain-relieving, and bruxism-reducing properties. Methods: The Research Diagnostic Criteria for Temporomandibular Disorders (RDC/TMDs) was utilized as the diagnostic framework. Sixty patients completed the study, which followed a parallel-group, three-arm, randomized, double-blind clinical trial design, with a 1:1:1 allocation ratio across three groups: 1a, 1b, and 2. Groups 1a and 1b received CBD formulations at concentrations of 10% and 5%, respectively, while Group 2 received a placebo formulation. The trial consisted of four main visits, namely screening, baseline, first follow-up after 14 days, and second follow-up after 30 days, during which surface electromyography (sEMG), the visual analogue scale (VAS) for pain assessment, and Bruxoff examinations were conducted. Results: The reduction in pain, as measured by the visual analogue scale (VAS), among patients using the 10% CBD formulation was 57.4% (p < 0.05), accompanied by a decrease in sEMG activity by 42.1% (p < 0.05). Conversely, individuals using the 5% CBD formulation experienced a 40.8% (p < 0.05) decrease in pain. Regarding the decrease in the sleep bruxism index, users of the 10% CBD formulation saw the highest reduction of 51% (p < 0.05). These findings underscore the efficacy of the proposed treatment in both experimental groups, with a notable advantage observed in Group 1a. Conversely, the outcomes of the selected variables for the control group did not exhibit significant differences throughout the study. Conclusions: The intraoral use of CBD formulations in patients with TMDs have proven to be a successful treatment for reducing pain, muscle tension, and bruxing activity in individuals with sleep bruxism and muscle-related TMDs. Specifically, a concentration of 10% CBD has demonstrated superior results compared to 5% CBD.

Computational ensemble expert system classification for the recognition of bruxism using physiological signals

This study aimed to develop an automatic diagnostic scheme for bruxism, a sleep-related disorder characterized by teeth grinding and clenching. The aim was to improve on existing methods, which have been proven to be inefficient and challenging. We utilized a novel hybrid machine learning classifier, facilitated by the Weka tool, to diagnose bruxism from biological signals. The study processed and examined these biological signals by calculating the power spectral density. Data were categorized into normal or bruxism categories based on the EEG channel (C4-A1), and the sleeping phases were classified into wake (w) and rapid eye movement (REM) stages using the ECG channel (ECG1-ECG2). The classification resulted in a maximum specificity of 93% and an accuracy of 95% for the EEG-based diagnosis. The ECG-based classification yielded a supreme specificity of 87% and an accuracy of 96%. Furthermore, combining these phases using the EMG channel (EMG1-EMG2) achieved the highest specificity of 95% and accuracy of 98%. The ensemble Weka tool combined all three physiological signals EMG, ECG, and EEG, to classify the sleep stages and subjects. This integration increased the specificity and accuracy to 97% and 99%, respectively. This indicates that a more precise bruxism diagnosis can be obtained by including all three biological signals. The proposed method significantly improves bruxism diagnosis accuracy, potentially enhancing automatic home monitoring systems for this disorder. Future studies may expand this work by applying it to patients for practical use.

Association between Psychological Distress and Possible, Probable, and Definite Sleep Bruxism-A Comparison of Approved Diagnostic Procedures

(1) Background: The relationship between sleep bruxism (SB) and psychological distress has been investigated in numerous studies and is heterogeneous. Different diagnostic procedures have been applied to determine SB. The aim of this study was to directly compare the association between psychological distress and SB diagnosed by different accepted methods. (2) Methods: Data of N = 45 subjects were analyzed, including group comparisons and correlation analyses. Following diagnostic methods for the determination of SB were used in one sample: self-report, clinical assessment, polysomnography with audio-video recording and a novel diagnostic sheet with analyzing software. Psychological distress was measured using the global severity index (GSI) of the Symptom Checklist-90-Standard (SCL-90-S). (3) Results: The GSI did not differ significantly between subjects with and without SB, regardless of the underlying diagnostic classification (p > 0.05). In-depth correlation analyses of self-report and clinical data revealed a weak-to-medium correlation with the GSI (r = 0.12-0.44). Due to non-normally distributed data, a test of statistical significance was not possible. Variables of instrumental methods such as the SB index (amount of SB activity per hour) of polysomnography (PSG) showed almost no correlation with psychological distress (r = -0.06-0.05). (4) Conclusions: Despite these limitations, the results provide an indication that the choice of diagnostic procedure may elucidate the variance in the correlation between SB and psychological distress.

Study Regarding the Monitoring of Nocturnal Bruxism in Children and Adolescents Using Bruxoff Device

Bruxism is a parafunctional activity represented by the gnashing and clenching of one's teeth. The aim of this study was to determine the utility of screening and monitoring with a Bruxoff device during nocturnal bruxism in 51 children and adolescents (36 with bruxism and 15 without bruxism) by assessing the variations in the intensity and duration of parafunctional activity in each patient. Bruxoff measurements were recorded for at least 60 min for three consecutive nights for each subject. All the parameters recorded using Bruxoff in the control and the study groups showed a statistically significant difference (p < 0.05). The differences found by comparing the values recorded in the male and female study groups are significant for heart rate, the number of masseter muscle contractions during one night, and mixed contractions. The Bruxoff device proved to be important in diagnosing patients with bruxism in our practice.

Is camera recording crucial for the correct diagnosis of sleep bruxism in polysomnography?

Due to potential issues, several sleep laboratories conduct sleep bruxism diagnosis without the use of a camera, instead relying mostly on electromyographic monitoring. The purpose of the study was to determine if a camera is necessary for the polysomnographic evaluation of sleep bruxism and how sleep bruxism parameters change when a camera is not utilised. The study material was actual polysomnographic recordings made in the years 2017-2020. A total of 199 single-night video-polysomnographic recordings of patients who were suspected of having sleep bruxism were chosen at random. The first analysis involved the evaluation of the video recording, while in the second video recording was not used. The findings revealed that all the examined sleep bruxism indices had statistically significantly higher values for the recordings made without the use of a camera. According to the findings, noncamera recordings had decreased sensitivity and specificity when the criteria of bruxism and mild-to-moderate bruxism were taken into account, and decreased sensitivity in the case of the criterion of severe bruxism. Sleep efficiency, the apnea/hypopnea index, and arousals had independent effects on the bruxism episode index value in the analysis of noncamera recordings. In conclusion, camera-based polysomnography still appears to be the most reliable way to assess the severity of sleep bruxism, particularly in patients who also report other sleep disturbances. The presence of symptoms of sleep-disordered breathing, insomnia, or other sleep disorders should prompt us to use camera-based diagnostics.

Correlation between a Force-Sensing Oral Appliance and Electromyography in the Detection of Tooth Contact Bruxism Events

Background: Oral appliances embedding sensors can be interesting tools for monitoring tooth contact bruxism in a home environment, as they address some of the usability limitations of portable electromyography (EMG) systems. In this study, an oral appliance for sleep bruxism monitoring was compared to an electromyograph. Methods: Simulated bruxism events with tooth contact, specifically clenching and grinding, and other occlusal activities unrelated to bruxism, were measured in 23 subjects with the two instruments simultaneously. The recordings were analyzed automatically by a computer program in order to compare the two techniques. Results: The two instruments were found to be strongly correlated in terms of detecting events (r = 0.89), and estimating their duration (r = 0.88) and their intensity (r = 0.83). Conclusions: The two techniques were in agreement in measuring event frequency, duration and intensity in the studied group, suggesting that force-sensing oral appliances have the potential to be easy-to-use tools for home monitoring of bruxism, alone or as complements to portable EMGs.

Variability of sleep bruxism-findings from consecutive nights of monitoring

OBJECTIVES

To determine sleep bruxism (SB) behavior during five consecutive nights and to identify correlations between SB episodes per hour (SB index) and sleep-time masseter-muscle activity (sMMA).

MATERIAL AND METHODS

Thirty-one participants were included in the study. Of these, 10 were classified as sleep bruxers (group SB-1) and nine as non-sleep bruxers (group non-SB). The bruxism status of these 19 patients was identified by means of questionnaires, an assessment of clinical symptoms, and electromyographic/electrocardiographic data (Bruxoff® device). The remaining 12 participants were also identified as bruxers, but based exclusively on data from the Bruxoff device (group SB-2). Data analysis included descriptive statistics and Spearman's correlation to assess the relationship between the SB index and sMMA.

RESULTS

Participants in group SB-1 showed an overall mean SB index of 3.1 ± 1.6 and a mean total sMMA per night of 62.9 ± 38.3. Participants in group SB-2 had an overall mean SB index of 2.7 ± 1.5 and a mean total sMMA of 56.0 ± 29.3. In the non-SB group, participants showed an overall mean SB index of 0.8 ± 0.5 and a mean total sMMA of 56.8 ± 30.3. Spearman's correlation yielded values of - 0.27 to 0.71 for the correlation between sMMA and SB index.

CONCLUSIONS

The data revealed variable SB activity and the absence of a reliable correlation between sMMA and the SB index.

CLINICAL RELEVANCE

The high variation in SB activity and lack of correlation between sMMA and the SB index should be considered when diagnosing SB.

TRIAL REGISTRATION

Clinical Trials [NIH], clinical trial no. NCT03039985.

An International Survey on Temporomandibular Joint Surgeon's Implementation and Management of Discectomy in Treating Temporomandibular Joint Internal Derangement

PURPOSE

To survey temporomandibular joint (TMJ) surgeons to determine current practice trends and perceptions regarding the role of discectomy for the treatment of TMJ internal derangements.

METHODS

An anonymous 5-part web-based survey was sent to TMJ surgeons. The survey was created and distributed, and the data were collected with the University of Michigan Qualtrics platform. Responses were compared based on operative volume, tendency to replace the disc, and likelihood of requiring temporomandibular joint replacement (TJR) after discectomy. Spearman correlations were used to test statistically significant differences. Domain-level analyses were also performed by summarizing items into 3 domain scores. Analyses were performed in SAS V9.4 (SAS Institute Inc., Cary, NC, USA).

RESULTS

Fifty-nine surgeons (33.9%) completed the survey. Discectomy was not considered to be a useful procedure by 85% of respondents, and 74% would not consider discectomy as a first surgical option. Most would consider discectomy (64%) before alloplastic total joint replacement. Discectomy was preferred over discopexy for the management of anterior disc displacement with reduction by high volume surgeons (89%), but most (72%) did not feel that discectomy was beneficial over arthroscopy in the treatment of anterior disc displacement without reduction and concomitant degenerative bony changes. In managing symptomatic disc perforation, 66% agreed that discectomy is the procedure of choice and 49% felt that interpositional tissue is indicated in most cases after discectomy. Respondents who reported fewer re-operations requiring alloplastic TJR after discectomy had, on average, more positive perceptions of discectomy on the benefits domain (P = .03), better than alternatives domain (P = .03), and fewer concerns on the perceived adverse effects domain (P = .03).

CONCLUSIONS

TMJ surgeons do not employ TMJ discectomy in most cases of TMJ internal derangement. However, discectomy is considered useful in cases of disc perforation or for persistent symptomatic disc displacement without reduction, in an attempt to avoid alloplastic TJR. Common adverse effects included joint noises and osteoarthrosis, and the use of interpositional disc replacement tissue did not alter the incidence of adverse effects or complications reported.

Pressure Algometry Evaluation of Two Occlusal Splint Designs in Bruxism Management-Randomized, Controlled Clinical Trial

The aim of this pilot study was to evaluate the short-term effectiveness of two different occlusal devices and their impact on the pressure pain threshold (PPT) values among patients who reported to the Dental Prosthetics Outpatient Clinic of Pomeranian Medical University (Szczecin, Poland) and who were diagnosed with probable bruxism. Two groups were formed (A and B) to which patients were assigned randomly. Each group used a different occlusal splint for bruxism management. The occlusal appliance by Okeson, or the bimaxillary splint, was used overnight by each patient for 30 days of the study. The PPT was measured twice, at the first visit and after 30 days of using each occlusal device, with Wagner Paintest FPX 25 algometer. Bruxism was diagnosed based on data from the patient's medical history and from the physical examination. Nocturnal Bruxism Criteria according to the International Classification of Sleep Disorders (Third Edition) was used for the patient's evaluation. Results: similar pain factor (PF) reduction was observed in both the examined groups, regardless of the device used; canine guidance and no guidance were similarly effective in terms of increasing pain resilience.

Research routes on improved sleep bruxism metrics: Toward a standardised approach

A recent report from the European Sleep Research Society's task force "Beyond AHI" discussed an issue that has been a long-term subject of debate - what are the best metrics for obstructive sleep apnoea (OSA) diagnosis and treatment outcome assessments? In a similar way, sleep bruxism (SB) metrics have also been a recurrent issue for >30 years and there is still uncertainty in dentistry regarding their optimisation and clinical relevance. SB can occur alone or with comorbidities such as OSA, gastroesophageal reflux disorder, insomnia, headache, orofacial pain, periodic limb movement, rapid eye movement behaviour disorder, and sleep epilepsy. Classically, the diagnosis of SB is based on the patient's dental and medical history and clinical manifestations; electromyography is used in research and for complex cases. The emergence of new technologies, such as sensors and artificial intelligence, has opened new opportunities. The main objective of the present review is to stimulate the creation of a collaborative taskforce on SB metrics. Several examples are available in sleep medicine. The development of more homogenised metrics could improve the accuracy and refinement of SB assessment, while moving forward toward a personalised approach. It is time to develop SB metrics that are relevant to clinical outcomes and benefit patients who suffer from one or more possible negative consequences of SB.

Artificial Intelligence Analysis of Mandibular Movements Enables Accurate Detection of Phasic Sleep Bruxism in OSA Patients: A Pilot Study

PURPOSE

Sleep bruxism (SBx) activity is classically identified by capturing masseter and/or temporalis masticatory muscles electromyographic activity (EMG-MMA) during in-laboratory polysomnography (PSG). We aimed to identify stereotypical mandibular jaw movements (MJM) in patients with SBx and to develop rhythmic masticatory muscles activities (RMMA) automatic detection using an artificial intelligence (AI) based approach.

PATIENTS AND METHODS

This was a prospective, observational study of 67 suspected obstructive sleep apnea (OSA) patients in whom PSG with masseter EMG was performed with simultaneous MJM recordings. The system used to collect MJM consisted of a small hardware device attached on the chin that communicates to a cloud-based infrastructure. An extreme gradient boosting (XGB) multiclass classifier was trained on 79,650 10-second epochs of MJM data from the 39 subjects with a history of SBx targeting 3 labels: RMMA episodes (n=1072), micro-arousals (n=1311), and MJM occurring at the breathing frequency (n=77,267).

RESULTS

Validated on unseen data from 28 patients, the model showed a very good epoch-by-epoch agreement (Kappa = 0.799) and balanced accuracy of 86.6% was found for the MJM events when using RMMA standards. The RMMA episodes were detected with a sensitivity of 84.3%. Class-wise receiver operating characteristic (ROC) curve analysis confirmed the well-balanced performance of the classifier for RMMA (ROC area under the curve: 0.98, 95% confidence interval [CI] 0.97-0.99). There was good agreement between the MJM analytic model and manual EMG signal scoring of RMMA (median bias -0.80 events/h, 95% CI -9.77 to 2.85).

CONCLUSION

SBx can be reliably identified, quantified, and characterized with MJM when subjected to automated analysis supported by AI technology.

A Novel Hybrid Machine Learning Classification for the Detection of Bruxism Patients Using Physiological Signals

Bruxism is a sleep disorder in which the patient clinches and gnashes their teeth. Bruxism detection using traditional methods is time-consuming, cumbersome, and expensive. Therefore, an automatic tool to detect this disorder will alleviate the doctor workload and give valuable help to patients. In this paper, we targeted this goal and designed an automatic method to detect bruxism from the physiological signals using a novel hybrid classifier. We began with data collection. Then, we performed the analysis of the physiological signals and the estimation of the power spectral density. After that, we designed the novel hybrid classifier to enable the detection of bruxism based on these data. The classification of the subjects into “healthy” or “bruxism” from the electroencephalogram channel (C4-A1) obtained a maximum specificity of 92% and an accuracy of 94%. Besides, the classification of the sleep stages such as the wake (w) stage and rapid eye movement (REM) stage from the electrocardiogram channel (ECG1-ECG2) obtained a maximum specificity of 86% and an accuracy of 95%. The combined bruxism classification and the sleep stages classification from the electroencephalogram channel (C4-P4) obtained a maximum specificity of 90% and an accuracy of 97%. The results show that more accurate bruxism detection is achieved by exploiting the electroencephalogram signal (C4-P4). The present work can be applied for home monitoring systems for bruxism detection.

Effect of laterotrusive occlusal scheme on chewing duration, external intercostal muscular activity, heart rate, and oxygen saturation

Objective: To evaluate the effect of the laterotrusive occlusal scheme on chewing duration, external intercostal (EIC) electromyographic (EMG) activity, heart rate (HR), and oxygen saturation (OS) during different tasks in the upright seated position.Methods: Fifty young participants, 25 with canine guidance and 25 with group function, were included. Chewing duration, bilateral EIC EMG activity, HR, and OS were recorded during the following tasks: 1) chewing until swallowing threshold; 2) laterotrusive teeth grinding.Results: Chewing duration, bilateral EIC EMG activity, HR, and OS showed no significant differences between the two laterotrusive occlusal schemes during the tasks studied.Conclusion: These results suggest that chewing duration, EIC muscle activity, HR, and OS were not significantly influenced by the laterotrusive occlusal scheme. Therefore, when a modification of the laterotrusive occlusal scheme is needed during oral rehabilitation or orthodontic treatment, canine guidance or group function should not significantly change EMG activity of EIC muscles.

Correlations between Sleep Bruxism and Temporomandibular Disorders

The aim of this study was to identify correlations between sleep bruxism (SB) and temporomandibular disorders (TMD) as diagnosed by means of the research diagnostic criteria for temporomandibular disorders (RDC/TMD). Sleep bruxism was diagnosed on the basis of I) validated questionnaires, II) clinical symptoms, and III) electromyographic/electrocardiographic data. A total of 110 subjects were included in the study. Fifty-eight patients were identified as bruxers and 52 as nonbruxers. A psychosocial assessment was also performed. An RDC/TMD group-I diagnosis (myofascial pain) was made for 10 out of 58 bruxers, whereas none of the nonbruxers received a diagnosis of this type. No significant differences were found between bruxers and nonbruxers with regard to RDC/TMD group-II (disc displacement) and group-III (arthralgia, arthritis, arthrosis) diagnoses. Somatization was significantly more common among bruxers than nonbruxers. Multivariate logistic regression analysis revealed that somatization was the only factor significantly correlated with the diagnosis of myofascial pain. The results of this study indicate a correlation between myofascial pain, as diagnosed using the RDC/TMD, and somatization. It seems that somatization is a stronger predictor of an RDC/TMD diagnosis of myofascial pain than sleep bruxism is.

Relationship between Sleep Bruxism, Perceived Stress, and Coping Strategies

Sleep bruxism (SB) is a common phenomenon defined as a masticatory muscle activity during sleep. Untreated severe SB can have significant dental and orofacial consequences. SB has often been linked with stress and maladaptive coping strategies. Therefore, in this study, a potential correlation between SB, perceived stress and coping strategies was evaluated. A total of 60 adults were enrolled into this study. Participants underwent a detailed intra- and extraoral exam focused on detecting bruxism symptoms. Additionally, the overnight Bruxism Index was recorded using the Bruxoff device. A total of 35 participants with symptoms of bruxism were assigned to the study group, whereas 25 asymptomatic participants were assigned to the control group. The Perceived Stress Scale (PSS-10) was used for stress assessment and Brief-COPE for coping strategies. Results showed that the higher the PSS-10 score, the higher the Bruxism Index was in the study group. Positive coping strategies were chosen most frequently in the control group, while maladaptive ones were chosen in the study group. It can be concluded that there is a relationship between perceived stress and sleep bruxism. Moreover, the type of coping strategies used by participants may have an impact on sleep bruxism, but the relationship should be further investigated.