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Paper Abstract and Keywords
Presentation 2024-03-01 11:10
Estimation of salivary secretion volume using near-infrared spectroscopy
Ryosuke Tsukagoshi, Yoshiko Sueda (Meisei Univ.) IN2023-98
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, the number of patients with dry mouth has been increasing due to causes such as diabetes, stress, and aging. When the symptoms of dry mouth worsen, there is a possibility of developing eating disorders, taste disorders, and speech disorders. It is important to conduct examinations before these disorders occur to enable early detection. Conventional methods for examination include Magnetic Resonance Imaging (MRI), the Saxon test, and saliva collection tests. However, these methods require appointments at hospitals, are expensive, and may cause physical stress because saliva cannot be swallowed easily. Therefore, this study aims to realize a model for estimating saliva secretion volume using sensors that are easy to use in daily life and can assess the status of salivary gland function without directly taking saliva. When comparing machine learning models trained by multiple individuals with the model trained using data from a single individual, the model trained by multiple people had better accuracy in estimating saliva volume. Experiments to change the number of individuals involved in training revealed that at least 10 individuals’ data are necessary to train the model, and around 15 to 18 individuals’ data are required to achieve sufficient accuracy. We compared the sensor values of the parotid region with those of the sublingual region. It showed no correlation between the two, indicating the difficulty of using data from the sublingual region for machine learning.
Keyword (in Japanese) (See Japanese page) 
(in English) IoT / light sensor / NIRS / Dry mouth / / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 398, IN2023-98, pp. 195-200, Feb. 2024.
Paper # IN2023-98 
Date of Issue 2024-02-22 (IN) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF IN2023-98

Conference Information
Committee NS IN  
Conference Date 2024-02-29 - 2024-03-01 
Place (in Japanese) (See Japanese page) 
Place (in English) Okinawa Convention Center 
Topics (in Japanese) (See Japanese page) 
Topics (in English) General 
Paper Information
Registration To IN 
Conference Code 2024-02-NS-IN 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Estimation of salivary secretion volume using near-infrared spectroscopy 
Sub Title (in English)  
Keyword(1) IoT  
Keyword(2) light sensor  
Keyword(3) NIRS  
Keyword(4) Dry mouth  
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1st Author's Name Ryosuke Tsukagoshi  
1st Author's Affiliation Meisei University (Meisei Univ.)
2nd Author's Name Yoshiko Sueda  
2nd Author's Affiliation Meisei University (Meisei Univ.)
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Speaker Author-1 
Date Time 2024-03-01 11:10:00 
Presentation Time 25 minutes 
Registration for IN 
Paper # IN2023-98 
Volume (vol) vol.123 
Number (no) no.398 
Page pp.195-200 
#Pages 6 
Date of Issue 2024-02-22 (IN) 

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