Introduction Bruxism remains a diagnostic challenge, with no consistently reliable clinical approaches available to document the condition with satisfactory accuracy. This study aimed to incorporate a biosensor device into a conventional bite-night guard to detect bruxism in an in vitro setting. Methods A sandwich-layering process was used to integrate stress and vibration sensors into an acrylic occlusal stabilization splint. The system included a microcontroller, control unit, and data acquisition module. Occlusal force signals were processed using artificial intelligence-based algorithms. A total of 200 repeated trials were conducted to evaluate system performance. Accuracy, sensitivity, and specificity were calculated as validation metrics. Results The biosensor prototype demonstrated reliable performance across a force range of 274–700 N. Quantitative evaluation of the neural network yielded an accuracy of 91%, sensitivity of 88%, and specificity of 90% in distinguishing occlusal force thresholds. Conclusion The findings confirm the feasibility of integrating biosensors within an intraoral appliance for bruxism detection in vitro . Future research should explore long-term durability testing in moist environments and conduct in vivo trials to validate clinical performance.
Al-Hamad et al. (Wed,) studied this question.