{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T05:07:10Z","timestamp":1788930430233,"version":"build-2803163510"},"reference-count":74,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2026,9,6]],"date-time":"2026-09-06T00:00:00Z","timestamp":1788652800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Sleep bruxism is the rhythmic or nonrhythmic masticatory muscle activity that occurs during sleep. It is conventionally diagnosed by a rule-based algorithm. Candidate muscle bursts are flagged against a fixed electromyographic (EMG) amplitude threshold, classified by duration into phasic, tonic, or mixed episodes, and counted into an hourly rate compared against a second threshold. These thresholds generalize poorly across individuals and nights. This has motivated a growing body of artificial intelligence (AI) research aimed at replacing one or more stages of this classical algorithm with a learned decision function. This paper synthesizes that literature as a technical pipeline across 28 reviewed AI-based sleep bruxism studies, identified through Web of Science and Google Scholar searches for \u201csleep bruxism\u201d combined with artificial intelligence terms, conducted in 2026, and screened for a learned, trained classification approach reported in English. These accuracy figures should be read alongside several complicating factors. Ten studies draw on the same subset of two patients from a public polysomnography database. Several studies framed as sleep bruxism detection were validated only on awake, simulated grinding. In addition, the ground-truth labels these classifiers are trained against remain contested within the field\u2019s own consensus literature. The paper\u2019s contribution is therefore twofold. It assembles the pipeline synthesis itself, spanning ground truth, recording modality, preprocessing, feature extraction, and architecture, as a technical reference not previously brought together in this form. It also uses that synthesis to set a concrete research agenda, including validation benchmarks across nights and across subjects, a shift from binary toward continuous severity targets, and an extension of detection into real-time treatment devices and clinical prognosis.<\/jats:p>","DOI":"10.3390\/diagnostics16172865","type":"journal-article","created":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T09:23:37Z","timestamp":1788773017000},"page":"2865","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Artificial Intelligence for Sleep Bruxism Detection: A Technical Pipeline Synthesis"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6698-4159","authenticated-orcid":false,"given":"\u00d6zge","family":"\u00c7ekirge","sequence":"first","affiliation":[{"name":"Department of Electrical and Electronics Engineering, Faculty of Engineering, Tarsus University, 33400 Mersin, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1111\/joor.12011","article-title":"Bruxism Defined and Graded: An International Consensus","volume":"40","author":"Lobbezoo","year":"2013","journal-title":"J. Oral Rehabil."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Zieli\u0144ski, G., Paj\u0105k, A., and W\u00f3jcicki, M. (2024). Global Prevalence of Sleep Bruxism and Awake Bruxism in Pediatric and Adult Populations: A Systematic Review and Meta-Analysis. J. Clin. Med., 13.","DOI":"10.3390\/jcm13144259"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1007\/s00784-018-2431-0","article-title":"Association of Sleep Bruxism with Oral Health-Related Quality of Life and Sleep Quality","volume":"23","year":"2019","journal-title":"Clin. Oral Investig."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1016\/j.adaj.2023.12.004","article-title":"Sleep bruxism: The past, the present, and the future\u2014Evolution of a concept","volume":"155","author":"Thomas","year":"2024","journal-title":"J. Am. Dent. Assoc."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Manfredini, D., and Lobbezoo, F. (2026). The Biopsychosocial Model of Bruxism. CRANIO\u00ae, 1\u20139.","DOI":"10.1080\/08869634.2026.2655187"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1080\/08869634.2021.1904181","article-title":"Influence of Genetics and Biopsychosocial Aspects as Etiologic Factors of Bruxism","volume":"39","author":"Caivano","year":"2021","journal-title":"CRANIO\u00ae"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"443","DOI":"10.5664\/jcsm.10348","article-title":"Sleep Bruxism Is Highly Prevalent in Adults with Obstructive Sleep Apnea: A Large-Scale Polysomnographic Study","volume":"19","author":"Li","year":"2023","journal-title":"J. Clin. Sleep Med."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.sleep.2021.11.008","article-title":"Associations between Sleep Bruxism and Other Sleep-Related Disorders in Adults: A Systematic Review","volume":"89","author":"Kuang","year":"2022","journal-title":"Sleep Med."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"e70046","DOI":"10.1002\/snz2.70046","article-title":"Sleep Bruxism: A Narrative Review of Current Concepts, Mechanisms, and Clinical Implications","volume":"56","author":"Balasubramaniam","year":"2026","journal-title":"J. R. Soc. N. Z."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"546","DOI":"10.1177\/00220345960750010601","article-title":"Sleep Bruxism: Validity of Clinical Research Diagnostic Criteria in a Controlled Polysomnographic Study","volume":"75","author":"Lavigne","year":"1996","journal-title":"J. Dent. Res."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"e476","DOI":"10.1055\/s-0044-1800887","article-title":"2024 Position Statement on the Use of Different Diagnostic Methods for Sleep Disorders in Adults\u2014Brazilian Sleep Association","volume":"17","author":"Palombini","year":"2024","journal-title":"Sleep Sci."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Vitazkova, D., Kosnacova, H., Turonova, D., Foltan, E., Jagelka, M., Berki, M., Micjan, M., Kokavec, O., Gerhat, F., and Vavrinsky, E. (2025). Transforming Sleep Monitoring: Review of Wearable and Remote Devices Advancing Home Polysomnography and Their Role in Predicting Neurological Disorders. Biosensors, 15.","DOI":"10.3390\/bios15020117"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Mogavero, M.P., Lanza, G., Bruni, O., Ferini-Strambi, L., Silvani, A., Faraguna, U., and Ferri, R. (2025). Beyond the Sleep Lab: A Narrative Review of Wearable Sleep Monitoring. Bioengineering, 12.","DOI":"10.3390\/bioengineering12111191"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"846","DOI":"10.1111\/joor.13170","article-title":"Signal Acquisition and Analysis of Ambulatory Electromyographic Recordings for the Assessment of Sleep Bruxism: A Scoping Review","volume":"48","author":"Thymi","year":"2021","journal-title":"J. Oral Rehabil."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1007\/s11325-014-0986-9","article-title":"Diagnostic Accuracy of Sleep Bruxism Scoring in Absence of Audio-Video Recording: A Pilot Study","volume":"19","author":"Carra","year":"2015","journal-title":"Sleep Breath."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"e13858","DOI":"10.1111\/jsr.13858","article-title":"Is Camera Recording Crucial for the Correct Diagnosis of Sleep Bruxism in Polysomnography?","volume":"32","author":"Smardz","year":"2023","journal-title":"J. Sleep Res."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"893","DOI":"10.1007\/s11325-019-01915-2","article-title":"Polysomnographic Scoring of Sleep Bruxism Events Is Accurate Even in the Absence of Video Recording but Unreliable with EMG-Only Setups","volume":"24","author":"Miettinen","year":"2020","journal-title":"Sleep Breath."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"17044","DOI":"10.1038\/s41598-025-01687-8","article-title":"The Effect of the Arousal Threshold on Sleep Bruxism Intensity in Coexisting Sleep Apnea and Sleep Bruxism: A Polysomnographic Study","volume":"15","author":"Martynowicz","year":"2025","journal-title":"Sci. Rep."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1912","DOI":"10.1111\/joor.14046","article-title":"Bruxism in Completely Edentulous Patients: A Scoping Review","volume":"52","author":"Orlandi","year":"2025","journal-title":"J. Oral Rehabil."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Al-Ayyad, M., Owida, H.A., de Fazio, R., Al-Naami, B., and Visconti, P. (2023). Electromyography Monitoring Systems in Rehabilitation: A Review of Clinical Applications, Wearable Devices and Signal Acquisition Methodologies. Electronics, 12.","DOI":"10.3390\/electronics12071520"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1111\/j.1365-2869.1997.00259.x","article-title":"Reliability of Scoring EMG Orofacial Events: Polysomnography Compared with Ambulatory Recordings","volume":"6","author":"Gallo","year":"1997","journal-title":"J. Sleep Res."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1139","DOI":"10.5664\/jcsm.3152","article-title":"Is There a First Night Effect on Sleep Bruxism? A Sleep Laboratory Study","volume":"9","author":"Hasegawa","year":"2013","journal-title":"J. Clin. Sleep Med."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1377","DOI":"10.5664\/jcsm.7278","article-title":"Home Polysomnography Reveals a First-Night Effect in Patients With Low Sleep Bruxism Activity","volume":"14","author":"Miettinen","year":"2018","journal-title":"J. Clin. Sleep Med."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"106100","DOI":"10.1016\/j.compbiomed.2022.106100","article-title":"A Review of Automated Sleep Disorder Detection","volume":"150","author":"Xu","year":"2022","journal-title":"Comput. Biol. Med."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Gan, C., and Yao, D. (2025). Artificial Intelligence in Sleep Bruxism Diagnosis and Treatment. Proceedings of the 2025 5th International Conference on Internet of Things and Machine Learning, Nanchang, China, 16 May 2025, ACM.","DOI":"10.1145\/3749566.3749604"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"837","DOI":"10.1111\/joor.12663","article-title":"International Consensus on the Assessment of Bruxism: Report of a Work in Progress","volume":"45","author":"Lobbezoo","year":"2018","journal-title":"J. Oral Rehabil."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"623","DOI":"10.1111\/joor.13626","article-title":"Five Years after the 2018 Consensus Definitions of Sleep and Awake Bruxism: An Explanatory Note","volume":"51","author":"Manfredini","year":"2024","journal-title":"J. Oral Rehabil."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1335","DOI":"10.1111\/joor.13985","article-title":"Updating the Bruxism Definitions: Report of an International Consensus Meeting","volume":"52","author":"Verhoeff","year":"2025","journal-title":"J. Oral Rehabil."},{"key":"ref_29","unstructured":"Iber, C., Ancoli-Israel, S., Chesson, A., and Quan, S.F. (2007). The AASM Manual for the Scoring of Sleep and Associated Events: Rules, Terminology and Technical Specifications, American Academy of Sleep Medicine."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1221","DOI":"10.29271\/jcpsp.2024.10.1221","article-title":"Diagnosis of bruxism in adults: A systematic review","volume":"34","author":"Raja","year":"2024","journal-title":"J. Coll. Physicians Surg. Pak."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Wang, C., Verma, A.K., Guragain, B., Xiong, X., and Liu, C. (2024). Classification of Bruxism Based on Time-Frequency and Nonlinear Features of Single Channel EEG. BMC Oral Health, 24.","DOI":"10.1186\/s12903-024-03865-y"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"102542","DOI":"10.1109\/ACCESS.2019.2928020","article-title":"Sleep Bruxism Detection Using Decision Tree Method by the Combination of C4-P4 and C4-A1 Channels of Scalp EEG","volume":"7","author":"Heyat","year":"2019","journal-title":"IEEE Access"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"88086","DOI":"10.1109\/ACCESS.2024.3409441","article-title":"Detection of bruxism using inverse discrete wavelet transformed reconstructed band limited EEG signals by group wise feature ranking","volume":"12","author":"Khan","year":"2024","journal-title":"IEEE Access"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"100469","DOI":"10.1016\/j.measen.2022.100469","article-title":"Supervised Approach Based Sleep Disorder Detection Using Non\u2014Linear Dynamic Features (NLDF) of EEG","volume":"24","author":"Tiwari","year":"2022","journal-title":"Meas. Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"046064","DOI":"10.1088\/1741-2552\/abf773","article-title":"An Automatic Sleep Disorder Detection Based on EEG Cross-Frequency Coupling and Random Forest Model","volume":"18","author":"Dimitriadis","year":"2021","journal-title":"J. Neural Eng."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Bin Heyat, M.B., Akhtar, F., Khan, A., Noor, A., Benjdira, B., Qamar, Y., Abbas, S.J., and Lai, D. (2020). A Novel Hybrid Machine Learning Classification for the Detection of Bruxism Patients Using Physiological Signals. Appl. Sci., 10.","DOI":"10.3390\/app10217410"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"e25958","DOI":"10.1016\/j.heliyon.2024.e25958","article-title":"Computational Ensemble Expert System Classification for the Recognition of Bruxism Using Physiological Signals","volume":"10","author":"Tripathi","year":"2024","journal-title":"Heliyon"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Piritu, D.A.I., and Taralunga, D.D. (2025). Robust Sleep Bruxism Detection Using Multimodal Physiological Signal Classification and Crossdataset Machine Learning. Proceedings of the 2025 IEEE 31st International Symposium for Design and Technology in Electronic Packaging (SIITME), Brasov, Romania, 22 October 2025, IEEE.","DOI":"10.1109\/SIITME67657.2025.11293510"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"82553","DOI":"10.1109\/ACCESS.2019.2924181","article-title":"Prognosis of Sleep Bruxism Using Power Spectral Density Approach Applied on EEG Signal of Both EMG1-EMG2 and ECG1-ECG2 Channels","volume":"7","author":"Lai","year":"2019","journal-title":"IEEE Access"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"101868","DOI":"10.1016\/j.measen.2025.101868","article-title":"High-fidelity EEG feature-engineered taxonomy for bruxism and PLMS prognostication through pioneering and avant-garde ML frameworks","volume":"39","author":"Tiwari","year":"2025","journal-title":"Meas. Sens."},{"key":"ref_41","unstructured":"Kidwai, M.S., and Khan, M.Z. (2021). A new perspective of detecting and classifying neurological disorders through recurrence and machine learning classifiers. Proceedings of the 2021 International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), IEEE."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Gul, J.Z., Fatima, N., Din, Z.M.U., Khan, M., Kim, W.Y., and Rehman, M.M. (2024). Advanced Sensing System for Sleep Bruxism across Multiple Postures via EMG and Machine Learning. Sensors, 24.","DOI":"10.3390\/s24165426"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"15503","DOI":"10.1109\/ACCESS.2025.3532360","article-title":"Wearable Regionally Trained AI-Enabled Bruxism-Detection System","volume":"13","author":"Ishtiaq","year":"2025","journal-title":"IEEE Access"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1109\/JSEN.2021.3128246","article-title":"An Intraoral Non-Occlusal MEMS Sensor for Bruxism Detection","volume":"22","author":"Cogan","year":"2022","journal-title":"IEEE Sens. J."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"e70619","DOI":"10.1111\/cns.70619","article-title":"Artificial Intelligence-Driven Hemodynamic Monitoring of Simulated Bruxism Using Functional Near-Infrared Spectroscopy: A Preliminary Study","volume":"31","author":"Fatima","year":"2025","journal-title":"CNS Neurosci. Ther."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Shen, Q., Cui, Y., Yang, J., Jing, X., Feng, Z., and Jin, S. (2026). Bruxism Recognition via Wireless Signal. ICC 2026\u2014IEEE International Conference on Communications, IEEE.","DOI":"10.1109\/ICC59461.2026.11588112"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"443","DOI":"10.1038\/s41598-025-29679-8","article-title":"A New Approach for the Field Detection of Sleep Bruxism Based on Inertial Sensor Data and Machine Learning Classification","volume":"16","author":"Schlaepfer","year":"2026","journal-title":"Sci. Rep."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"e2420498122","DOI":"10.1073\/pnas.2420498122","article-title":"A Deep Learning\u2013Enabled Smart Garment for Accurate and Versatile Monitoring of Sleep Conditions in Daily Life","volume":"122","author":"Tang","year":"2025","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"7874254","DOI":"10.1155\/ijod\/7874254","article-title":"Experimental analysis of automatic discrimination performance between simulated bruxism and non-bruxism under conscious conditions using electromyography and machine learning","volume":"2026","author":"Minakuchi","year":"2026","journal-title":"Int. J. Dent."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"102905","DOI":"10.1016\/j.bspc.2021.102905","article-title":"Machine Learning and Regression Analysis for Diagnosis of Bruxism by Using EMG Signals of Jaw Muscles","volume":"69","author":"Sonmezocak","year":"2021","journal-title":"Biomed. Signal Process. Control"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"11","DOI":"10.5755\/j02.eie.28838","article-title":"Detection of EMG Signals by Neural Networks Using Autoregression and Wavelet Entropy for Bruxism Diagnosis","volume":"27","author":"Sonmezocak","year":"2021","journal-title":"Elektron. IR Elektrotechnika"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"476","DOI":"10.1080\/21681163.2022.2079003","article-title":"Detection of Lower Jaw Activities from Micro Vibration Signals of Masseter Muscles Using MEMS Accelerometer","volume":"11","author":"Kurt","year":"2023","journal-title":"Comput. Methods Biomech. Biomed. Eng. Imaging Vis."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"994","DOI":"10.1109\/JBHI.2013.2274532","article-title":"Use of Electromyographic and Electrocardiographic Signals to Detect Sleep Bruxism Episodes in a Natural Environment","volume":"17","author":"Castroflorio","year":"2013","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"1449","DOI":"10.2147\/NSS.S320664","article-title":"Artificial Intelligence Analysis of Mandibular Movements Enables Accurate Detection of Phasic Sleep Bruxism in OSA Patients: A Pilot Study","volume":"13","author":"Martinot","year":"2021","journal-title":"Nat. Sci. Sleep"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"40413","DOI":"10.1109\/ACCESS.2025.3546720","article-title":"An Artificial Intelligence-Based Approach With Photoplethysmogram and Heart Rate Variability for Sleep Bruxism Diagnosis","volume":"13","author":"Eris","year":"2025","journal-title":"IEEE Access"},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Orhan, K., Yazici, G., \u00d6nder, M., Evli, C., Volkan-Yazici, M., Kolsuz, M.E., Ba\u011f\u0131\u015f, N., Kafa, N., and G\u00f6n\u00fclda\u015f, F. (2024). Development and Validation of an Ultrasonography-Based Machine Learning Model for Predicting Outcomes of Bruxism Treatments. Diagnostics, 14.","DOI":"10.3390\/diagnostics14111158"},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Takamura, R., Li, Y., Hamasaki, T., and Nakatoh, Y. (2025). A study on the detection of sleep bruxism using acoustic features. Proceedings of the 2025 IEEE International Symposium on Consumer Technology (ISCT), IEEE.","DOI":"10.1109\/ISCT66099.2025.11297374"},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Peruzzi, G., Galli, A., and Pozzebon, A. (2022). A Novel Methodology to Remotely and Early Diagnose Sleep Bruxism by Leveraging on Audio Signals and Embedded Machine Learning. Proceedings of the 2022 IEEE International Symposium on Measurements & Networking (M&N), Padua, Italy, 18 July 2022, IEEE.","DOI":"10.1109\/MN55117.2022.9887782"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"101906","DOI":"10.1016\/j.smrv.2024.101906","article-title":"Instrumental Assessment of Sleep Bruxism: A Systematic Review and Meta-Analysis","volume":"74","year":"2024","journal-title":"Sleep Med. Rev."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1080\/08869634.2020.1815392","article-title":"Portable and Wearable Electromyographic Devices for the Assessment of Sleep Bruxism and Awake Bruxism: A Literature Review","volume":"41","author":"Yamaguchi","year":"2023","journal-title":"CRANIO\u00ae"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"722","DOI":"10.1111\/joor.12520","article-title":"Validity of Different Tools to Assess Sleep Bruxism: A Meta-analysis","volume":"44","author":"Casett","year":"2017","journal-title":"J. Oral Rehabil."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"S53","DOI":"10.1111\/adj.13057","article-title":"Ambulatory Devices to Detect Sleep Bruxism: A Narrative Review","volume":"69","author":"Li","year":"2024","journal-title":"Aust. Dent. J."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"e65272","DOI":"10.2196\/65272","article-title":"Wearable Artificial Intelligence for Sleep Disorders: Scoping Review","volume":"27","author":"Aziz","year":"2025","journal-title":"J. Med. Internet Res."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"369","DOI":"10.1007\/s41060-023-00407-7","article-title":"Sound-Based Sleep Assessment with Controllable Subject-Dependent Embedding Using Variational Domain Adversarial Neural Network","volume":"20","author":"Fukui","year":"2025","journal-title":"Int. J. Data Sci. Anal."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"e70001","DOI":"10.1002\/cre2.70001","article-title":"Toward wearables for bruxism detection: Voluntary oral behaviors sound recorded across the head depend on transducer placement","volume":"10","author":"Nahhas","year":"2024","journal-title":"Clin. Exp. Dent. Res."},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Alfieri, D., Awasthi, A., Belcastro, M., Barton, J., O\u2019Flynn, B., and Tedesco, S. (2021). Design of a Wearable Bruxism Detection Device. Proceedings of the 2021 32nd Irish Signals and Systems Conference (ISSC), Athlone, Ireland, 10 June 2021, IEEE.","DOI":"10.1109\/ISSC52156.2021.9467867"},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Flores-Ram\u00edrez, B., Suaste-G\u00f3mez, E., Garc\u00eda-Lim\u00f3n, V., and Angeles-Medina, F. (2025). Flexible PVDF Sensors for Bruxism Bite Force Measurement: A Redefined Instrumental Approach. PLoS ONE, 20.","DOI":"10.1371\/journal.pone.0330422"},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Tajitsu, Y., Shimda, S., Nonomura, T., Yanagimoto, H., Nakamura, S., Ueshima, R., Kawanobe, M., Nakiri, T., Takarada, J., and Takeuchi, O. (2023). Application of Braided Piezoelectric Poly-l-Lactic Acid Cord Sensor to Sleep Bruxism Detection System with Less Physical or Mental Stress. Micromachines, 15.","DOI":"10.3390\/mi15010086"},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Gao, J., Liu, L., Gao, P., Zheng, Y., Hou, W., and Wang, J. (2019). Intelligent Occlusion Stabilization Splint with Stress-Sensor System for Bruxism Diagnosis and Treatment. Sensors, 20.","DOI":"10.3390\/s20010089"},{"key":"ref_70","doi-asserted-by":"crossref","unstructured":"Al-Hamad, K.A., Asiri, A., Al-Qahtani, A.M., Alotaibi, S., and Almalki, A. (2025). Development and In-Vitro Validation of an Intraoral Wearable Biofeedback System for Bruxism Management. Front. Bioeng. Biotechnol., 13.","DOI":"10.3389\/fbioe.2025.1572970"},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1111\/joor.13577","article-title":"A Worldwide Bibliometric Analysis of the Research Trends and Hotspots of Bruxism in Adults during 1991\u20132021","volume":"51","author":"Zhong","year":"2024","journal-title":"J. Oral Rehabil."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"828","DOI":"10.1002\/mus.21262","article-title":"Time\u2013Frequency Analysis of Rhythmic Masticatory Muscle Activity","volume":"39","author":"Farella","year":"2009","journal-title":"Muscle Nerve"},{"key":"ref_73","doi-asserted-by":"crossref","unstructured":"Moxley, B., Stevens, W., Sneed, J., and Pearl, C. (2023). Novel Diagnostic and Therapeutic Approaches to Temporomandibular Dysfunction: A Narrative Review. Life, 13.","DOI":"10.3390\/life13091808"},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Bondareva, E., Hauksd\u00f3ttir, E.R., and Mascolo, C. (2021). Earables for Detection of Bruxism: A Feasibility Study. Proceedings of the Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers, Virtual, 21 September 2021, ACM.","DOI":"10.1145\/3460418.3479327"}],"container-title":["Diagnostics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2075-4418\/16\/17\/2865\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T04:20:23Z","timestamp":1788927623000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2075-4418\/16\/17\/2865"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,6]]},"references-count":74,"journal-issue":{"issue":"17","published-online":{"date-parts":[[2026,9]]}},"alternative-id":["diagnostics16172865"],"URL":"https:\/\/doi.org\/10.3390\/diagnostics16172865","relation":{},"ISSN":["2075-4418"],"issn-type":[{"value":"2075-4418","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,6]]}}}