Development of intraoral sensors for the continuous measurement of clinically relevant parameters in the oral cavity

A strong understanding of bio-adhesion, bio-mineralization, and metabolic processes in the oral cavity is crucial for maintaining oral health. Metabolic processes in the oral cavity are influenced by the diverse environment of oral fluids with its complex composition. Real-time monitoring is challenging due to heterogeneous composition variations across sampling volumes and secretion variability within different regions of the mouth.

The development of a multi-sensor devices for continuous monitoring within the oral cavity aims to integrate flexible sensors into dental splints to monitor glucose, pH, lactate, calcium, phosphate, and fluoride concentrations in saliva.

The sensing device, embedded into a personalized splint features four electrochemical sensors and one open circuit potentiometry sensor for pH measurements. Controlled by a low-power microcontroller handling data collection and control.

For pH-sensors, a potentiometric measurement mode was chosen. Ag/AgCl reference electrode (RE) was covered with a solid-state layer of polyvinylbutyrate (PVB) and the working electrode (WE) was functionalized with polyaniline (PANI) via electrodeposition.

The pH measurements were conducted by open circuit potentiometry. A linear response with -53.8mV/pH was achieved. Unstimulated saliva samples from different volunteers were applied and the pH values determined by our sensors fitted well the pH values measured by a commercial electrode.

Continuous in vitro measurements of glucose and lactate followed amperometric sensing approaches . Electrochemical sensors were fabricated by applying oxidases and Prussian blue onto the WE while incorporating chitosan. The prepared sensors were tested in solutions with varying analytes and were conducted with the developed intraoral electronics.

The detection of additional parameters such as calcium, phosphate and fluoride are subject of current research. The collected data can be displayed in real-time on a mobile device and forwarded to cloud storage for post-processing. This approach enables real-time monitoring of important parameters for oral disease development.