Swallowing function evaluation using deep-learning-based acoustic signal processing

Chisa Kodama, Kunihito Kato, Satoshi Tamura, Satoru Hayamizu

研究成果: Conference contribution

抄録

In recent years, people with swallowing disorder are increasing. Therefore, it is important to evaluate the swallowing function in the early detection and prevention of swallowing disorder. In this study, we used a capsule that generates sound and estimated the timing at which food is sent to the esophagus by sound signal processing and deep learning. By comparing it with the movement of the epiglottis tracked by the image, we performed a noninvasive and quantitative swallowing function evaluation.

本文言語English
ホスト出版物のタイトルProceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017
出版社Institute of Electrical and Electronics Engineers Inc.
ページ961-964
ページ数4
ISBN(電子版)9781538615423
DOI
出版ステータスPublished - 2018 2 5
外部発表はい
イベント9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017 - Kuala Lumpur, Malaysia
継続期間: 2017 12 122017 12 15

出版物シリーズ

名前Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017
2018-February

Other

Other9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017
国/地域Malaysia
CityKuala Lumpur
Period17/12/1217/12/15

ASJC Scopus subject areas

  • 人工知能
  • 人間とコンピュータの相互作用
  • 情報システム
  • 信号処理

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