Implementation of Sensor Technology in Smart Denture Design: A Targeted Response to Occlusal Trauma and Monitoring Deficiencies Among Rural Denture Users in Nigeria

Abstract

Nigerian rural communities experience premature removable denture loss since dental practitioners fail to identify occlusal trauma post-denture delivery which allows stress-induced teeth bruxism to develop and coincides with inadequate follow-up dental care. This document explains a digitally validated smart denture system which resolves the addressed problem. The standard acrylic denture base contains 12-point quantitative pressure sensors together with a cortisol biosensor. Through Bluetooth Low Energy (BLE) the system transmits dental pressure data and stress information to mobile storage where they securely reside in blockchain databases for remote analysis. A machine learning model performs an occlusion anomaly classification of unilateral posture overload and bruxism during simulated cycles with an accuracy of more than 96%. The detection of cortisol enables monitoring of stress-driven bite patterns that show direct correlation to simulated bruxism manifestations. Such an intelligent denture solution offers a scalable method to monitor post-insertion dental patients in areas without access to clinical services through elimination of direct patient assessments. Early trauma assessment combined with trauma reduction and digital workflows between providers and patients receives support from this technology.