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

Jinxia Gao; Longjun Liu; Peng Gao; Yihuan Zheng; Wenxuan Hou; Junhui Wang

doi:10.3390/s20010089

journal article Open Access Dec 22, 2019

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

Jinxia Gao Longjun Liu

Peng Gao

Yihuan Zheng Wenxuan Hou Junhui Wang

Sensors Vol. 20 No. 1 pp. 89 · MDPI AG

View at Publisher Save 10.3390/s20010089

Abstract

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.

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References

Details

Published: Dec 22, 2019
Vol/Issue: 20(1)
Pages: 89
License: View

Authors

J

Jinxia Gao

Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, College of Stomatology, Xi’an Jiaotong University, Xi’an 710004, China; Department of Prothodontics, College of Stomatology, Xi’an Jiaotong University, Xi’an 710004, China

L

Longjun Liu