Development of wireless bruxism monitoring device based on pressure-sensitive polymer composite

Kim, Jung Ho; McAuliffe, Padraig; O’Connell, Brian; Diamond, Dermot; Lau, King Tong

doi:10.1016/j.sna.2010.08.033

Cited by 9 publications

(10 citation statements)

References 17 publications

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“…Details of the design and assembly of the sensor‐containing splint have been published . The force sensor was placed within a clear acrylic splint, with the sensor material buried approximately 1 mm below the occlusal surface in the pre‐molar/first molar region (Fig.…”

Section: Methodsmentioning

confidence: 99%

A sleep bruxism detection system based on sensors in a splint – pilot clinical data

McAuliffe

Kim

Diamond

et al. 2014

J of Oral Rehabilitation

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SUMMARY It is difficult in a dental setting to accurately diagnose sleep bruxism and to objectively assess the severity, frequency or natural history of the condition in an individual patient. Yet this information is essential for the management of sleep bruxism and to plan appropriate dental treatment. The objective of this study was to clinically test a device that could be used to record bruxism events in a home environment. Pressure sensors were developed for use under the surface of an occlusal splint, and circuitry was designed to facilitate the recording and wireless transmission of the pressure sensor signal to a computer. Controlled mandibular movements were carried out in vivo to simulate bruxism and non-bruxism patterns. These patterns of force application were graphically presented to two examiners who were asked to identify the type of activity represented by the force curves. Examiners were largely able to distinguish bruxism from non-bruxism activity; the sensitivity ranged from 80% to 100% and the specificity from 75% to 100%. Using sensors in an occlusal splint, it is possible to recognise the typical tooth contact patterns seen in sleep bruxism. Such a device may be useful for monitoring sleep bruxism over an extended period at home.

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Section: Methodsmentioning

confidence: 99%

A sleep bruxism detection system based on sensors in a splint – pilot clinical data

McAuliffe

Kim

Diamond

et al. 2014

J of Oral Rehabilitation

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“…Instead of relying on an EMG‐based device, authors applied a pressure‐oriented oral appliance to directly measure SB activity. As previously stated, the surface EMG signals can be affected by a number of factors including electrode position, posture and skin resistance. As a matter of fact, the device used in the study has shown great results in detecting SB events when authors simultaneously compared it with PSG.…”

Section: Discussionmentioning

confidence: 99%

“…Instead of relying on an EMG-based device, authors applied a pressure-oriented oral appliance to directly measure SB activity. As previously stated, 36 The environment surrounding the subjects during the recording night was different (sleep laboratory vs home).…”

Section: Sato Et Al (2014)mentioning

confidence: 99%

Efficacy of biofeedback therapy on sleep bruxism: A systematic review and meta‐analysis

Jokubauskas

Baltrušaitytė

2018

J of Oral Rehabilitation

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This study updates the review published by Wang et al in 2014 (Sleep Breath 2014;18(2):235-242). The review focuses on the most recent literature on management of sleep bruxism (SB) with biofeedback. An electronic search was conducted in five databases searching for articles published later than the date of Wang et al's search, viz., October 2012. Six articles of 2320 identified citations involving 86 adult participants were included in the qualitative synthesis. Of them, 4 were randomised controlled trials (RCTs) and 2 were uncontrolled before-after studies. Different feedback modalities (electrical, auditory and vibratory stimulus) were investigated. The overall quality of the selected studies was assessed using the GRADE criteria. Due to heterogeneity between studies, the quantitative synthesis was performed out of three RCTs, of which two were retrieved from the previous review. The meta-analysis indicated a non-significant difference in electromyographic-measured SB episodes per hour after one night of contingent electrical stimulation (CES) compared with placebo control, yet a significant difference was shown after five nights of CES. The quality of evidence identified through GRADEpro was from low to moderate, due to imprecision and inconsistency between studies. Qualitative synthesis did not present a reliable reduction in clinical pain levels; however, no substantial sleep disturbances were indicated following the intervention. In conclusion, one of the biofeedback modalities, CES, is effective in reducing SB-related motor activities after a short-term treatment period. However, evidence of long-term effects is lacking. Further longitudinal studies with larger samples are necessary to acknowledge the clinical application of biofeedback.

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“…Tartaglia 1 , C. Sforza 1 , D. Farina 3 tends to substantially overestimate SB episodes. Furthermore some diagnostic devices based on dental contact detection have been introduced with promising results (17,18,19). Interestingly, recent studies show that the SB event is preceded by a sudden shift in autonomic cardiac and respiratory activity, and by a specific brain activation (12) that suggests overactivation of the autonomic system as closely related to the pathogenesis of SB (8,11,12).…”

Section: Use Of Electromyographic and Electrocardiographic Signals Tomentioning

confidence: 99%

Use of Electromyographic and Electrocardiographic Signals to Detect Sleep Bruxism Episodes in a Natural Environment

Castroflorio

Mesin

Tartaglia

et al. 2013

IEEE J. Biomed. Health Inform.

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Diagnosis of bruxism is difficult since not all contractions of masticatory muscles during sleeping are bruxism episodes. In this paper, we propose the use of both EMG and ECG signals for the detection of sleep bruxism. Data have been acquired from 21 healthy volunteers and 21 sleep bruxers. The masseter surface EMGs were detected with bipolar concentric electrodes and the ECG with monopolar electrodes located on the clavicular regions. Recordings were made at the subjects' homes during sleeping. Bruxism episodes were automatically detected as characterized by masseter EMG amplitude greater than 10% of the maximum and heart rate increasing by more than 25% with respect to baseline within 1 s before the increase in EMG amplitude above the 10% threshold. Furthermore, the subjects were classified as bruxers and nonbruxers by a neural network. The number of bruxism episodes per night was 24.6 ± 8.4 for bruxers and 4.3 ± 4.5 for controls ( P < 0.0001). The classification error between bruxers and nonbruxers was 1% which was substantially lower than when using EMG only for the classification. These results show that the proposed system, based on the joint analysis of EMG and ECG, can provide support for the clinical diagnosis of bruxism.

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Development of wireless bruxism monitoring device based on pressure-sensitive polymer composite

Cited by 9 publications

References 17 publications

A sleep bruxism detection system based on sensors in a splint – pilot clinical data

A sleep bruxism detection system based on sensors in a splint – pilot clinical data

Efficacy of biofeedback therapy on sleep bruxism: A systematic review and meta‐analysis

Use of Electromyographic and Electrocardiographic Signals to Detect Sleep Bruxism Episodes in a Natural Environment

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