{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:22:09Z","timestamp":1760059329013,"version":"build-2065373602"},"reference-count":47,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2025,6,6]],"date-time":"2025-06-06T00:00:00Z","timestamp":1749168000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"JST Moonshot R&amp;D Program","award":["JPMJMS239F"],"award-info":[{"award-number":["JPMJMS239F"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Saliva is an important secretion, and a continued insufficient amount of saliva secreted causes glossitis, stomatitis, and so on. Since the amount of saliva secreted changes daily, adverse effects occur daily. Therefore, it is necessary to constantly measure the amount of saliva secreted and take appropriate measures when it decreases. However, there is no method to constantly measure saliva. We propose a method to estimate the amount of saliva secreted from the sound acquired by a wearable throat microphone. The proposed method uses deep learning to classify whether the sound acquired by the throat microphone is swallowing or not. Based on the swallowing information, the proposed method estimates the amount of saliva secreted. The accuracy of the classification of swallowing was 96.96%. For the estimation of the amount of saliva secreted, the R was 0.600 and MAE was 0.0487.<\/jats:p>","DOI":"10.3390\/s25123584","type":"journal-article","created":{"date-parts":[[2025,6,6]],"date-time":"2025-06-06T09:43:14Z","timestamp":1749202994000},"page":"3584","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Method for Estimating Amount of Saliva Secreted Using a Throat Microphone"],"prefix":"10.3390","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-4255-1706","authenticated-orcid":false,"given":"Kai","family":"Washino","sequence":"first","affiliation":[{"name":"Graduate School of Engineering, Kobe University, 1-1 Rokkodaicho, Nada, Kobe 657-8501, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3583-6118","authenticated-orcid":false,"given":"Ayumi","family":"Ohnishi","sequence":"additional","affiliation":[{"name":"Graduate School of Engineering, Kobe University, 1-1 Rokkodaicho, Nada, Kobe 657-8501, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2260-3788","authenticated-orcid":false,"given":"Tsutomu","family":"Terada","sequence":"additional","affiliation":[{"name":"Graduate School of Engineering, Kobe University, 1-1 Rokkodaicho, Nada, Kobe 657-8501, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8662-4070","authenticated-orcid":false,"given":"Masahiko","family":"Tsukamoto","sequence":"additional","affiliation":[{"name":"Graduate School of Engineering, Kobe University, 1-1 Rokkodaicho, Nada, Kobe 657-8501, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,6,6]]},"reference":[{"key":"ref_1","unstructured":"Edgar, W.M., O\u2019Mullane, D., and Dawes, C. 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