AR tooth brushing system to promote oral care
habits of children
Haruki Kondo

Kenji Funahashi

Nagoya Institute of Technology, Japanh.kondo.801@stn.nitech.ac.jp

Nagoya Institute of Technology, Japankenji@nitech.ac.jp

Index Terms—Tooth brushing, Children’s oral care, MachinelearningI. I NTRODUCTION
It is needed to be careful about the places where bacteria
can accumulate while brushing teeth [1]. But it is difﬁcult toteach young children to brush their teeth properly. By the way,
the system about hand-washing for children that superimposes
bacteria illustrations on the route of contact infection has been
proposed in our laboratory [2]. In this study, we propose new
AR system to promote oral care habits of children. It detects
tooth areas easily soiled in real time using machine learningtechnique ﬁrst, and superimposes bacteria illustrations to show
easily soiled areas. It is expected that children learn good toothbrushing habit.

Fig. 1. Appearance of experiment

II. S YSTEM CONFIGURATIONIn our proposed system, mouth and teeth image is taken by afront camera of PC ﬁrst. Then teeth are detected and extracted,especially molars, the areas between a tooth and gum, the areas
between a tooth and another tooth, and the area behind a front
tooth. Bacteria illustrations are superimposed there.
Machine learning library YOLOv3 [3] was used as follows,(1) to learn areas where teeth are easily soiled using 1523
images that may include other than mouth, (2) to learn areas
where teeth are easily soiled using 944 images that include
only mouth, and (3) to learn mouth areas using 1216 images
that include other than mouth. The f values are 0.340, 0.453,
and 0.980 respectively. The method detecting tooth after
detecting mouth is better than that detecting tooth from face
image directly. However, if mouth area can not be detectedfrom face image, teeth are tried to be detected directly. The
height size of superimposed bacteria illustration is twice aslarge as the height of the area, and it dose not overlap witheach other. If the system detects too large area to be tootharea, then does not show an illustration.
III. E XPERIMENT
It was conﬁrmed that the bacteria illustrations were superimposed appropriately (Fig. 1). The refresh rate is 2.04 fps. Twoelementary school students and their parents used this system(Fig. 2), and answered a questionnaire. Some impressions wereobtained as; (1) it was helpful to promote oral care habits ofchildren, (2) it encouraged them to brush their teeth every day,Fig. 2. Bacteria illustrationand (3) it was interesting because the bacteria were displayedon their tooth. The result showed that the system was so validthat children learn good tooth brushing habit.
IV. C ONCLUSION
In this paper, we proposed new AR system to promoteoral care habits of children. The bacteria illustrations weresuperimposed on appropriate tooth positions on camera image.
As future works, ﬁrst, we would like to improve the systemrefresh rate. Second, dark tooth images should be learned,
because the system may not detect tooth correctly when itis dark. Third, additional experiments are expected for more
homes and nurseries to conﬁrm usefulness.
V. ACKNOWLEDGEMENT
This work was supported by JSPS KAKENHI Grant Number JP20K11918.
R EFERENCES[1] Kozue Matsubara, Method for Tooth Brushing Oral Health Exercise,
Dental Medicine Research 31: 249-260 (2011).
[2] Syogo Shimada, Kenji Hunabashi, AR Germs Display System to Promote Pediatric Hand Hygiene Habits, Master’s thesis of Nagoya Instituteof Technology (2018).
[3] Joseph Redmon, Ali Farhadi, YOLOv3: An Incremental Improvement,
arXiv:1804.02767 (2018).