2015年
Evaluating Tooth Brushing Performance With Smartphone Sound Data
PROCEEDINGS OF THE 2015 ACM INTERNATIONAL JOINT CONFERENCE ON PERVASIVE AND UBIQUITOUS COMPUTING (UBICOMP 2015)
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- 開始ページ
- 109
- 終了ページ
- 120
- 記述言語
- 英語
- 掲載種別
- 研究論文(国際会議プロシーディングス)
- DOI
- 10.1145/2750858.2804259
- 出版者・発行元
- ASSOC COMPUTING MACHINERY
This paper presents a new method for evaluating tooth brushing performance using audio collected from a smartphone. To do this, we use hidden Markov models (HMMs) to recognize audio data that include various types of tooth brushing actions, such as brushing the outer surface of the front teeth and brushing the inner surface of the back teeth. We then use the output of the HMMs to build regression models to estimate tooth brushing performance scores, such as stroke quality of brushing for the back inner teeth and duration of brushing for the front teeth. The scores used to train these regression models are obtained from a dentist who specializes in dental care instruction, with the resulting regression models estimating performance scores that closely correspond to the scores assigned by the dentist.
- リンク情報
- ID情報
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- DOI : 10.1145/2750858.2804259
- Web of Science ID : WOS:000383742200010