ToMoBrush: Exploring Dental Health Sensing Using a Sonic Toothbrush
Authors: 
Kuang Yuan, 
Mohamed Ibrahim, Yiwen Song, Guoxiang Deng, Robert A. Nerone, Suvendra Vijayan, 
Akshay Gadre, Swarun KumarAuthors Info & Claims
Article No.: 139, Pages 1 - 27
Abstract
Early detection of dental disease is crucial to prevent adverse outcomes. Today, dental X-rays are currently the most accurate gold standard for dental disease detection. Unfortunately, regular X-ray exam is still a privilege for billions of people around the world. In this paper, we ask: "Can we develop a low-cost sensing system that enables dental self-examination in the comfort of one's home?"
This paper presents ToMoBrush, a dental health sensing system that explores using off-the-shelf sonic toothbrushes for dental condition detection. Our solution leverages the fact that a sonic toothbrush produces rich acoustic signals when in contact with teeth, which contain important information about each tooth's status. ToMoBrush extracts tooth resonance signatures from the acoustic signals to characterize the dental condition of each tooth. We further develop a data-driven signal processing pipeline to detect and discriminate different dental conditions. We evaluate ToMoBrush on 19 participants and dental-standard models for detecting common dental problems including caries, calculus, and food impaction, achieving a detection ROC-AUC of 0.90, 0.83, and 0.88 respectively. Interviews with dental experts further validate ToMoBrush's potential in enhancing at-home dental healthcare.
Supplemental Material
MP4 File - Introduction Video of ToMoBrush
- A video that presents the motivation of ToMoBrush and the hardware setup - A live demo on a dental model to detect food impaction
- Download
- 240.45 MB
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Published: 09 September 2024
Published in IMWUT Volume 8, Issue 3
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- African Engineering and Technology Network
- Cisco Systems
- Manufacturing Futures Institute
- Office of Naval Research
- Safety21
- Cylab-Enterprise
- National Science Foundation
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