School of Biomedical Engineering, College of Biomedical & Health Science, Konkuk University, Chung-Ju, Korea.
IEEE Trans Biomed Eng. 2012 Mar;59(3):872-81. doi: 10.1109/TBME.2011.2181369. Epub 2011 Dec 22.
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.
由于牙周病可能在早期发生，因此尽早养成正确的刷牙习惯非常重要。为此，提出了一种能够追踪刷牙动作和方向信息的智能牙刷（ST）的可行性和概念。在这项研究中，我们提出了先进的 ST 系统和刷牙区域分类算法。为了追踪口腔中牙刷的刷牙区域和方向，我们需要 ST 的绝对坐标信息。通过使用倾斜补偿方位（航向）算法，我们找到了牙刷的倾斜和方向信息，而在刷内侧牙齿表面时的方向信息具有特定的航向特征，可以可靠地区分与其他刷牙模式。为了评估所提出的 ST 在临床使用中的可行性，我们对 15 名健康个体的 16 个刷牙区域进行了研究。所提出的 ST 系统展示了 97.1%（±0.91）的区域检测准确性，并且可以对 15 个刷牙区域进行分类。这项研究还表明，所提出的 ST 系统可能有助于牙科保健人员对患者进行刷牙习惯的口腔卫生教育和指导。
