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Toothbrushing monitoring using wrist watch

  • Stony Brook University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

50 Scopus citations

Abstract

Daily toothbrushing is essential for maintaining oral health. However, there is very limited technology to monitor the effectiveness of toothbrushing at home. In this paper, a system is built to monitor the brushing quality on all 16 tooth surfaces using a manual toothbrush and an off-Theshelf wrist watch. The toothbrush is modified by attaching small magnets to the handle, so that its orientation and motion can be captured by the magnetic sensor in the wrist watch. The toothbrushing gestures are recognized based on inertial sensing data from the wrist watch. As the acoustic signal collected from the watch is correlated with the motion of toothbrushing stroke, acoustic sensing algorithm is designed to assist in recognition. User-specific toothbrushing order is also utilized to improve the surface recognition. In extensive experiments with 12 users over 3 weeks, our system successfully recognized toothbrushing gestures with an average precision of 85.6%.

Original languageEnglish
Title of host publicationProceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016
PublisherAssociation for Computing Machinery, Inc
Pages202-215
Number of pages14
ISBN (Electronic)9781450342636
DOIs
StatePublished - Nov 14 2016
Event14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016 - Stanford, United States
Duration: Nov 14 2016Nov 16 2016

Publication series

NameProceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016

Conference

Conference14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016
Country/TerritoryUnited States
CityStanford
Period11/14/1611/16/16

Keywords

  • Activity Recognition
  • Toothbrushing Monitoring
  • Wearables

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