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ToMoBrush: Exploring Dental Health Sensing using a Sonic Toothbrush

Kuang Yuan, Mohamed Ibrahim, Yiwen Song, Guoxiang Deng, Suvendra Vijayan, Robert Nerone, Akshay Gadre, Swarun Kumar

TL;DR

ToMoBrush is presented, a dental health sensing system that explores using off-the-shelf sonic toothbrushes for dental condition detection and develops a data-driven signal processing pipeline to detect and discriminate different dental conditions.

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 varied dental health conditions of the teeth. 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 validate ToMoBrush's potential in enhancing at-home dental healthcare.

ToMoBrush: Exploring Dental Health Sensing using a Sonic Toothbrush

TL;DR

ToMoBrush is presented, a dental health sensing system that explores using off-the-shelf sonic toothbrushes for dental condition detection and develops a data-driven signal processing pipeline to detect and discriminate different dental conditions.

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 varied dental health conditions of the teeth. 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 validate ToMoBrush's potential in enhancing at-home dental healthcare.
Paper Structure (21 sections, 11 equations, 15 figures)

This paper contains 21 sections, 11 equations, 15 figures.

Table of Contents

  1. Introduction
  2. Background of Dental Health Problems
  3. Related Work
  4. overview
  5. Tooth Signature Extraction
  6. Vibration Behavior Modeling
  7. Extraction Algorithm
  8. Feature Selection
  9. Health Detection
  10. Mitigating error factors
  11. Noise Suppression
  12. Sequence Alignment
  13. Implementation and Evaluation
  14. Technical Evaluation
  15. Data Collection Procedure
  16. ...and 6 more sections

Figures (15)

  • Figure 1: ToMoBrush is a dental health sensing tool composed of a commodity sonic toothbrush with a microphone integrated close to the brush head. It detects the changes in the resonances of teeth to enable dental health sensing.
  • Figure 2: System overview of ToMoBrush. (a) showcases the brushing segments of the lower-left quadrant in different colors. (b) shows the signal processing pipeline.
  • Figure 3: Signal spectra when a sonic toothbrush is vibrating alone vs. when in contact with a tooth. (a) shows brushing induces the resonances of the tooth. (b) shows brushing also changes the excitation signal itself.
  • Figure 4: The signal received by the microphone composed of the excitation signal directly from the toothbrush head as well as the tooth response
  • Figure 5: Examples of signal in log spectrum (denoised version) when the toothbrush is vibrating alone vs. brushing
  • ...and 10 more figures