Feng Hao, Song Wenhao, Li Ruyi, Yang Linxin, Chen Xiaoxuan, Guo Jiajun, Liao Xuan, Ni Lei, Zhu Zhou, Chen Junyu, Pei Xibo, Li Yijun, Wang Jian
State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, Department of Prosthodontics, West China Hospital of Stomatology, State Key Laboratory of Polymer Materials Engineering, Polymer Research Institute, Sichuan University, Chengdu, 610041, China.
Key Laboratory of Testing Technology for Manufacturing Process of Ministry of Education, Southwest University of Science and Technology, Mianyang, 621010, China.
Adv Sci (Weinh). 2025 Jan;12(2):e2411187. doi: 10.1002/advs.202411187. Epub 2024 Nov 19.
Currently, the diagnosis of malocclusion is a highly demanding process involving complicated examinations of the dental occlusion, which increases the demand for innovative tools for occlusal data monitoring. Nevertheless, continuous wireless monitoring within the oral cavity is challenging due to limitations in sampling and device size. In this study, by embedding high-performance piezoelectric sensors into the occlusal surfaces using flexible printed circuits, a fully integrated, flexible, and self-contained transparent aligner is developed. This aligner exhibits excellent sensitivity for occlusal force detection, with a broad detection threshold and continuous pressure monitoring ability at eight distinct sites. Integrated with machine learning algorithm, this fully integrated aligner can also identify and track adverse oral habits that can cause/exacerbate malocclusion, such as lip biting, thumb sucking, and teeth grinding. This system achieved 95% accuracy in determining malocclusion types by analyzing occlusal data from over 1400 malocclusion models. This fully-integrated sensing system, with wireless monitoring and machine learning processing, marks a significant advancement in the development of intraoral wearable sensors. Moreover, it can also facilitate remote orthodontic monitoring and evaluation, offering a new avenue for effective orthodontic care.
目前，错颌畸形的诊断是一个要求很高的过程，涉及复杂的牙合检查，这增加了对牙合数据监测创新工具的需求。然而，由于采样和设备尺寸的限制，口腔内的连续无线监测具有挑战性。在本研究中，通过使用柔性印刷电路将高性能压电传感器嵌入咬合面，开发了一种完全集成、柔性且独立的透明矫治器。该矫治器对咬合力检测具有出色的灵敏度，具有较宽的检测阈值，并能在八个不同部位进行连续压力监测。与机器学习算法集成后，这种完全集成的矫治器还可以识别和跟踪可能导致/加重错颌畸形的不良口腔习惯，如咬唇、吮拇指和磨牙。该系统通过分析1400多个错颌畸形模型的牙合数据，在确定错颌畸形类型方面达到了95%的准确率。这种具有无线监测和机器学习处理功能的完全集成传感系统，标志着口腔内可穿戴传感器发展的重大进步。此外，它还可以促进远程正畸监测和评估，为有效的正畸护理提供了一条新途径。
