Poster: Automated Tooth Brushing Detection Using Smartwatch
Source
Mobisys 2024 Proceedings of the 2024 22nd Annual International Conference on Mobile Systems Applications and Services
Date Issued
2024-06-03
Author(s)
Schleter, Blake
Avdonina, Marina
Adhikary, Rishiraj
Jaisinghani, Dheryta
Sen, Sougata
Abstract
Oral diseases affect an estimated 3.5 billion people globally, posing significant health challenges. According to the World Health Organization (WHO), adopting self-care practices and maintaining personal oral hygiene can substantially mitigate the prevalence of dental caries. While smartwatches have previously been utilized to track activities of daily living (ADL), their widespread availability has yet to be harnessed for accurately identifying tooth brushing activity among other common ADL. In this Work in Progress (WIP), we demonstrate how motion sensors integrated into smartwatches can effectively distinguish tooth brushing from seven other very similar ADL. We present our initial results that show a promising 94% accuracy with 84% sensitivity.
Subjects
activity recognition | machine learning | toothbrushing
