Bimodal Visual Sensors Based on Mechanoluminescence and Biosensing for Artificial Intelligence-Assisted Orthodontics

Abstract

Flexible visual sensors hold great potential for application in wearable electronics and health monitoring. However, the separate acquisition of various visual signals without mutual interference and their functional integration in internal biomedical devices remains a significant challenge. Here, a functional material that integrates mechanoluminescent units with biosensing units through supramolecular interactions, enabling bimodal non-interfering visual detection of orthodontic force and bacterial infection is presented. The orthodontic force induces fluorescence by facilitating the release of electrons from trapped energy levels, caused by the disruption or rearrangement of defect structures within strontium aluminate crystals. Meanwhile, the seamlessly integrated biosensing component can effectively detect lactic acid in a dose-dependent manner, underscoring its multifunctional capabilities in biosensing applications. Moreover, the development of a cloud-based deep learning server can achieve a 97.7% accuracy in the precise decoupling of visual signals, facilitating remote monitoring and enabling early intervention during orthodontic treatment. The proposed artificial intelligence-enhanced bimodal visual sensors represent a new paradigm for orthodontic monitoring, suitable for a wide range of biomedical applications.