| Presentation | 2024-03-01 Estimation of salivary secretion volume using near-infrared spectroscopy Ryosuke Tsukagoshi, Yoshiko Sueda, |
|---|---|
| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(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) |
| Keyword(in English) | IoT / light sensor / NIRS / Dry mouth |
| Paper # | IN2023-98 |
| Date of Issue | 2024-02-22 (IN) |
| Conference Information | |
| Committee | NS / IN |
|---|---|
| Conference Date | 2024/2/29(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Okinawa Convention Center |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | General |
| Chair | Tetsuya Oishi(NTT) / Kunio Hato(NTT) |
| Vice Chair | Takumi Miyoshi(Shibaura Inst. of Tech.) / Tsutomu Murase(Nagoya Univ.) |
| Secretary | Takumi Miyoshi(NTT) / Tsutomu Murase(Kogakuin Univ.) |
| Assistant | Hiroshi Yamamoto(NTT) |
| Paper Information | |
| Registration To | Technical Committee on Network Systems / Technical Committee on Information Networks |
|---|---|
| Language | JPN |
| 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 |
| 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.) |
| Date | 2024-03-01 |
| Paper # | IN2023-98 |
| Volume (vol) | vol.123 |
| Number (no) | IN-398 |
| Page | pp.pp.195-200(IN), |
| #Pages | 6 |
| Date of Issue | 2024-02-22 (IN) |