Sleep bruxism: an overview for clinicians

Liu

et al. 2019

Sensors

Bruxism is a masticatory muscle activity characterized by high prevalence, widespread complications, and serious consequences but without specific guidelines for its diagnosis and treatment. Although occlusal force-based biofeedback therapy is proven to be safe, effective, and with few side effects in improving bruxism, its mechanism and key technologies remain unclear. The purpose of this study was to research a real-time, quantitative, intelligent, and precise force-based biofeedback detection device based on artificial intelligence (AI) algorithms for the diagnosis and treatment of bruxism. Stress sensors were integrated and embedded into a resin-based occlusion stabilization splint by using a layering technique (sandwich method). The sensor system mainly consisted of a pressure signal acquisition module, a main control module, and a server terminal. A machine learning algorithm was leveraged for occlusal force data processing and parameter configuration. This study implemented a sensor prototype system from scratch to fully evaluate each component of the intelligent splint. Experiment results showed reasonable parameter metrics for the sensors system and demonstrated the feasibility of the proposed scheme for bruxism treatment. The intelligent occlusion stabilization splint with a stress sensor system is a promising approach to bruxism diagnosis and treatment.Sensors 2020, 20, 89 2 of 15 discussion summary, the existing assessment of bruxism could also be classified into three main aspects: (1) noninstrumental approaches, (2) instrumental approaches, and (3) cut-off points grading [6]. Self-report and clinical examination are considered as noninstrumental approaches, which are also the primary choices in the clinical assessment of bruxism. However, their reliability and validity need further improvement [6]. EMG may provide good evidence of both sleep and awake bruxism, but there is also a risk of overestimating the number of true SB events [7]. PSG could be regarded as a reference standard for SB assessment; however, it is expensive and time-consuming [2]. To date, the reliability and validity of all the common techniques remain debatable, and consensus has yet to be established regarding the best method to diagnose bruxism. Therefore, exploring some new methods of bruxism diagnosis and management is a necessary and meaningful research topic.The use of biofeedback technologies (electrical, auditory, vibratory stimulus, etc.) as behavioral techniques of bruxism diagnosis and treatment has been considered a promising approach in both clinical and scientific fields in recent years [8]. Various biofeedback modalities have been reported in previous papers, and most of these are based on EMG recordings, except two studies that described force-based devices [8,9]. An intra-splint force detector (ISFD) for SB force detection was described in 2003 [10]. A detailed description of this SB inhibition system has been presented in a recently published paper [11]. This inhibition system consisted of ISFD, vibration, and co...

Section: Sandwich Methodsmentioning

confidence: 99%

Section: Sandwich Methodsmentioning

confidence: 99%

Intelligent Occlusion Stabilization Splint with Stress-Sensor System for Bruxism Diagnosis and Treatment

Liu

et al. 2019

Sensors

“…That is why the current gold standard in diagnosing SB and for differential diagnosis is polysomnography [28]. This method combines electromyography, electroencephalography and audio-visual recordings of sleeping individuals, giving a wide range of accurate information [8]. The method is proven to be more accurate than selfreport or even third party report in SB [28].…”

Section: Sleep Bruxismmentioning

confidence: 99%

What should a dentist be aware of concerning symptoms of sleep disorders in the oral cavity?

Smardz¹,

Florjański²,

Orzeszek³

et al. 2019

jos

A B S T R AC TSleep bruxism (SB) is a common and complex phenomenon that can result in serious clinical consequences concerning the stomatognathic system including damage to dental hard tissues, especially tooth wear, damage to prosthetic restorations, damage to the periodontium and oral mucosa, and a spectrum of symptoms affecting masticatory muscles. However, there are other conditions with similar clinical manifestations that may resemble or even in some cases mimic SB. The aim of this study was to evaluate the most common sleep-related conditions that can cause clinical implications similar to SB and to emphasize the methods of carrying out a proper differential diagnosis. PubMed, Web of Science, and Scopus databases were searched for current literature on the manifestation of selected sleep disorders in the stomatognathic system. Forty-one articles were finally included in this review. Conditions such as oromandibular myoclonus, dystonia, Parkinson's disease and parkinsonism, epileptic and non-epileptic motor phenomena were included in this review as potentially mimicking the symptoms of sleep bruxism. Included studies indicate that the combination of accurate medical history interview, thorough clinical examination and video-polysomnography seems to be the key to proper differential diagnostics between SB and other medical conditions that can occur during sleep and present similar clinical symptoms affecting the stomatognathic system.

Adıyaman Üniversitesi Sağlık Bilimleri Dergisi

“…Bruksizm, dişlerin sıkılması veya gıcırdatılması ile karakterize tekrarlayan çene kas aktivitesi olarak tanımlanır (1,2). Bruksizmin uyku bruksizmi ve uyanık bruksizmi olmak üzere iki farklı tipi vardır.…”

unclassified

“…Bruksizmin uyku bruksizmi ve uyanık bruksizmi olmak üzere iki farklı tipi vardır. Farklı güvenilirliğe sahip metodolojilerin bir sonucu olarak bildirilen bruksizm prevelansı oldukça geniş bir aralığa (%5 ile %91) sahiptir (2,3). Bununla beraber uyku bruksizminin populasyonda genel olarak prevelansının %8 ile %13 arasında olduğu düşünülmektedir (2,4).…”

unclassified

Bruksizm Hastalarında Klinik Bulgularının Araştırılması

Yavuz

Bayazıt

2019

Bruksizm tanısı konulan hastalara ait klinik bulguların araştırılması amaçlanmıştır. Yöntem: Ocak 2018-Aralık 2018 tarihleri arasında Adıyaman Üniversitesi Diş Hekimliği Fakültesi Ağız, Diş ve Çene Cerrahisi kliniğine başvuran Amerikan Uyku Tıbbı Akademisi tanı kriterlerine göre uyku bruksizmi tanısı konulan 110 hasta çalışmaya dahil edildi. Bruksizm tanısı konulan hastaların klinik muayenesinde, dişlerde aşınma varlığı, dilin lateral kenarlarında diş izleri, yanak mukozasında ısırma sonucu oluşan linea alba varlığı, periodontal hastalık, dişlerde hassasiyet, çiğneme kaslarında ağrı, temporomandibular eklemde ağrı, masseter kaslarında hipertrofi ve baş ağrısı değerlendirildi. Bulgular: Yaş ortalaması 32.95±12.34 olan, 78'i kadın 32'si erkek olan uyku bruksizmi tanısı konulan 110 hasta çalışmaya dahil edildi. Bruksizm tanısı konulan 110 hastanın 81'inde (%73.6) dişlerin insizal yüzeylerinde aşınma, 70'inde (%63.6) dilin lateral kenarlarında girintiler, 55'inde (%50) yanak mukozasında linea alba varlığı, 29'unda (%26.4) periodontal hastalık, 29'unda (%26.4) diş hassasiyeti, 77'sinde (%70) çiğneme kaslarında ağrı, 67'sinde (%60.9) TME bölgesinde ağrı, 27'sinde (%24.5) masseter kaslarında hipertrofi, 53'ünde (%48.2) ise baş ağrısı bulunmaktaydı. Sonuç: Bruksizmli hastalarda klinik bulgulardan en fazla diş aşınması, daha sonra ise çiğneme kaslarında ağrı, dil lateral kenarlarında girinti ve TME ağrısı eşlik etmektedir.