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Dental plaque removal efficiency of a smart toothbrush based on augmented reality in children

증강현실 기반 스마트 칫솔의 치면세균막 제거효과 평가

  • Min-Ji Park (Department of Dental Hygiene, Dankook University) ;
  • Suk-Bin Jang (Division of Infectious Diseases, Departments of Internal Medicine, Dankook University Hospital, Dankook University College of Medicine) ;
  • Jae-Young Lee (Department of Dental Hygiene, Dankook University)
  • Received : 2023.01.09
  • Accepted : 2023.02.12
  • Published : 2023.02.28

Abstract

Objectives: Based on the strengths of augmented reality (AR), this study aimed to determine the dental plaque removal efficiency of a guided brushing program in children. Methods: This randomized, controlled, double-blind crossover clinical trial evaluated the plaque removal rate after regular brushing versus AR-based guided toothbrushing in 20 children aged 5-12 years. Results: Overall, the dental plaque removal efficiency of AR-based brushing was superior to that of regular brushing (p<0.05). When classified in detail, no significant difference was noted in the plaque removal rate between the two brushing methods in the anterior region (p=0.056), whereas a significant difference in the plaque removal rate was observed in the posterior region (p<0.05). Conclusions: Based on these results, the efficacy of dental plaque removal for brushing using an AR-based smartphone application was confirmed; thus, this can be used for oral health education incorporating ICT technology in the future.

연구목적: 본 연구는 스마트 폰을 활용한 증강현실의 기반의 칫솔질 가이드 프로그램을 이용하여 어린이의 치면세균막 제거 효율이 어떻게 변화하는지 알아보고자 하였다. 연구방법: 이중맹검 교차임상시험을 통하여, 5-12세 어린이 20명을 대상으로 일반 칫솔질 후 치면세균막 제거효율을 측정하고 워시아웃기간 이후, 증강현실 기반 칫솔질 수행 후 치면세균막 제거효율을 평가하여 비교하였다. 연구결과: 전반적으로 증강현실 기반 양치질이 일반 양치질보다 플라그 제거 효율이 우수하였다(p<0.05). 세부적으로 분류하면 전치부에서는 두 가지 칫솔질 방법 간 플라그 제거율에서 유의한 차이가 없었으나(p=0.056), 구치부에서는 플라그 제거율에서 유의한 차이가 있음을 확인하였다(p<0.05). 결론: 증강현실 기반을 기반으로 스마트폰을 이용한 양치질에 대한 치태 제거 효능을 확인하였으며, 향후 ICT 기술을 접목한 구강보건교육에 활용할 수 있을 것으로 판단된다.

Keywords

Acknowledgement

This research was funded by the National Research Foundation of Korea (NRF), grant number 2021R1F1A1064231. The NRF was funded by the Korean government (MSIT).

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