Toothbrushing region detection using three-axis accelerometer and magnetic sensor.

Abstract

Due to the possible occurrence of periodontal disease at an early age, it is important to have proper toothbrushing habits as early as possible. With this aim, the feasibility and concept of a smart toothbrush (ST) capable of tracing toothbrushing motion and orientation information was suggested. In this study, we proposed the advanced ST system and brushing region classification algorithm. In order to trace the brushing region and the orientation of a toothbrush in the mouth, we required the absolute coordinate information of ST. By using tilt-compensated azimuth (heading) algorithm, we found the inclination and orientation information of the toothbrush, and the orientation information while brushing inner tooth surfaces showed specific heading features that could be reliably discriminated from other brushing patterns. In order to evaluate the feasibility of clinical usage of the proposed ST, 16 brushing regions were investigated by 15 individual healthy subjects. The proposed ST system demonstrated 97.1%(±0.91) of the region detection accuracy and 15 brushing regions could be classified. This study also showed that the proposed ST system may be helpful for dental care personnel in patient education and instruction for oral hygiene regarding brushing habits.