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.

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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
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article

BrushBuds: Toothbrushing Tracking Using Earphone IMUs

Cecilia Mascolo, Dong Ma, Qiang Yang, Yang Liu et al.
2 citations
Context-Aware Activity Recognition Systems
0.50
article

BrushBuds: Toothbrushing Tracking Using Earphone IMUs

Cecilia Mascolo, Dong Ma, Qiang Yang, Yang Liu, Kayla-Jade Butkow, Jake Stuchbury-Wass
article en
2 citations

Abstract

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.

University of Cambridge (GB), Singapore Management University (SG)
Openalex Percentile: Top 35%
Context-Aware Activity Recognition Systems
0.50
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BrushBuds: Toothbrushing Tracking Using Earphone IMUs — Cecilia Mascolo, Dong Ma, et al. · (2024) | TGRS Research Map | TGRS