| Presentation | 2017-01-26 Estimation of respiratory state using machine learning Keisuke Matsuoka, Jiro Okuda, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Recent studies have tried to extract information on respiration from photoplethysmographic (PPG) signals. It is well known that the PPG signal includes respiratory synchronous components. In this study, we extracted feature information from the PPG signal measured at fingertip of 10 healthy subjects. We estimated respiratory states (inspiration / expiration) using machine learning algorithms including neural network, support vector machine, and k-means clustering. We also investigated influence of dimensional reduction of the features by using principal component analysis. We evaluated usefulness of respiratory state estimation by machine learning with PPG signals. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Photoplethysmography / Neural Network / Principal Component Analysis |
| Paper # | NC2016-53 |
| Date of Issue | 2017-01-19 (NC) |
| Conference Information | |
| Committee | NC / NLP |
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| Conference Date | 2017/1/26(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Kitakyushu Foundation for the Advanement of Ind. Sci. and Tech. |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Implementation of Neuro Computing,Analysis and Modeling of Human Science, etc |
| Chair | Shigeo Sato(Tohoku Univ.) / Hisato Fujisaka(Hiroshima City Univ.) |
| Vice Chair | Masafumi Hagiwara(Keio Univ.) / Masaharu Adachi(Tokyo Denki Univ.) |
| Secretary | Masafumi Hagiwara(Kyoto Sangyo Univ.) / Masaharu Adachi(Tokyo Inst. of Tech.) |
| Assistant | Hisanao Akima(Tohoku Univ.) / Yoshihisa Shinozawa(Keio Univ.) / Hiroyuki Asahara(Okayama Univ. of Science) / Toshihiro Tachibana(Shonan Inst. of Tech.) |
| Paper Information | |
| Registration To | Technical Committee on Neurocomputing / Technical Committee on Nonlinear Problems |
|---|---|
| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Estimation of respiratory state using machine learning |
| Sub Title (in English) | |
| Keyword(1) | Photoplethysmography |
| Keyword(2) | Neural Network |
| Keyword(3) | Principal Component Analysis |
| 1st Author's Name | Keisuke Matsuoka |
| 1st Author's Affiliation | Kyoto Sangyo University(Kyoto Sangyo Univ.) |
| 2nd Author's Name | Jiro Okuda |
| 2nd Author's Affiliation | Kyoto Sangyo University(Kyoto Sangyo Univ.) |
| Date | 2017-01-26 |
| Paper # | NC2016-53 |
| Volume (vol) | vol.116 |
| Number (no) | NC-424 |
| Page | pp.pp.31-36(NC), |
| #Pages | 6 |
| Date of Issue | 2017-01-19 (NC) |