Integrating Impedance Spectroscopy and Perceptron-Based Classification for Tooth Treatment Monitoring

The increasing prevalence of dental caries necessitates the development of advanced diagnostic tools that can accurately assess the stages of tooth demineralization and the efficacy of remineralization treatments. This study introduces a novel, non-invasive procedure using impedance spectroscopy coupled with an automatic classification algorithm based on a single perceptron topology to evaluate the demineralization and remineralization states of enamel. In-vitro experimental treatments were conducted on sound human dental samples, subjected to controlled demineralization and subsequent remineralization processes, employing cutting-edge nanoparticles designed to mimic natural remineralization mechanisms. The impedance measurement, known for its sensitivity to changes in electrical properties, was adapted to detect variations in the enamel's structure and composition, indicative of demineralization and remineralization. The perceptron-based classifier was able to properly differentiate between the various stages of enamel integrity showing quite promising results. The effectiveness and accuracy of the impedance spectroscopy and classification approach were further validated by Scanning Electron Microscopy and Raman spectroscopy analyses, which confirmed the morphological and chemical modifications within the enamel. These results not only validate the proposed method as a reliable tool for early detection of dental demineralization but also offer a promising approach for monitoring the effectiveness of remineralization therapies, thereby contributing to preventive dentistry and enhanced oral health care.