BrushBuds: Toothbrushing Tracking Using Earphone IMUs
Inadequate toothbrushing habits are a leading cause of oral health problems such as tooth decay. Many individuals are uncertain if they are brushing effectively or over-focusing on specific areas. While high-end electric toothbrushes can address these concerns, manual toothbrushes remain widely used due to their simplicity and affordability. In this paper, we introduce BrushBuds, an earphone-based toothbrushing monitoring system aimed at tracking brushing areas, which leverages the ubiquitous presence of earphones to enhance manual toothbrushing. BrushBuds utilizes Inertial Measurement Units (IMUs) in earphones to detect subtle head movements incurred by toothbrushing. By capturing distinct motion patterns specific to brushing for each tooth region, BrushBuds can effectively track the toothbrushing process. Our evaluation demonstrates the feasibility of BrushBuds, showing an average accuracy of 84.3% in identifying six distinct tooth areas. By enhancing manual toothbrushing with IMU sensors in earphones, BrushBuds has the potential to significantly improve oral hygiene practices for a broad range of manual toothbrush users.
Authors
- Cecilia Mascolo (ORCID: https://orcid.org/0000-0001-9614-4380)
- Dong Ma (ORCID: https://orcid.org/0000-0003-3824-234X)
- Qiang Yang (ORCID: https://orcid.org/0000-0002-5202-7892)
- Yang Liu (ORCID: https://orcid.org/0000-0002-2474-2004)
- Kayla-Jade Butkow (ORCID: https://orcid.org/0000-0002-5508-7188)
- Jake Stuchbury-Wass (ORCID: https://orcid.org/0000-0001-6733-0504)
Institutions
- University of Cambridge (GB)
- Singapore Management University (SG)
Publication Details
- Published
- 2024-09-22
- DOI
- https://doi.org/10.1145/3675094.3680521
- Citations
- 2
- Primary Topic
- Context-Aware Activity Recognition Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.50