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Support vector machines as multivariate calibration model for prediction of blood glucose concentration using a new non-invasive optical method named pulse glucometry
http://hdl.handle.net/2297/14390
http://hdl.handle.net/2297/143901be0e3ea-072a-41d3-b4df-fec09bb1fa7a
名前 / ファイル | ライセンス | アクション |
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TE-PR-OGAWA-M-4561.pdf (126.4 kB)
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Item type | 会議発表論文 / Conference Paper(1) | |||||
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公開日 | 2017-10-03 | |||||
タイトル | ||||||
タイトル | Support vector machines as multivariate calibration model for prediction of blood glucose concentration using a new non-invasive optical method named pulse glucometry | |||||
言語 | ||||||
言語 | eng | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_5794 | |||||
資源タイプ | conference paper | |||||
著者 |
Ogawa, Mitsuhiro
× Ogawa, Mitsuhiro× Yamakoshi, Yasuhiro× Satoh, Makoto× Nogawa, Masamichi× Yamakoshi, Takehiro× Tanaka, Shinobu× Rolfe, Peter× Tamura, Toshiyo× Yamakoshi, Ken-ichi |
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提供者所属 | ||||||
内容記述タイプ | Other | |||||
内容記述 | 金沢大学理工研究域機械工学系 | |||||
書誌情報 |
Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings 号 4353354, p. 4561-4563, 発行日 2007-01-01 |
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ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 0589-1019 | |||||
NCID | ||||||
収録物識別子タイプ | NCID | |||||
収録物識別子 | AA00782308 | |||||
DOI | ||||||
関連タイプ | isIdenticalTo | |||||
識別子タイプ | DOI | |||||
関連識別子 | 10.1109/IEMBS.2007.4353354 | |||||
出版者 | ||||||
出版者 | Institute of Electrical and Electronics Engineers (IEEE) | |||||
抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | A novel optical non-invasive in vivo blood glucose concentration (BGL) measurement technique, named "Pulse Glucometry", was combined with a kernel method; support vector machines. The total transmitted radiation intensity (Iλ) and the cardiac-related pulsatile changes superimposed on Iλ in human adult fingertips were measured over the wavelength range from 900 to 1700 nm using a very fast spectrophotometer, obtaining a differential optical density (ΔOD λ) related to the blood component in the finger tissues. Subsequently, a calibration model using paired data of a family of ΔODλs and the corresponding known BGLs was constructed with support vector machines regression instead of using calibration by a conventional partial least squares regression (PLS). Our results show that the calibration model based on the support vector machines can provide a good regression for the 183 paired data, in which the BGLs ranged from 89.0-219 mg/dl (4.94-12.2 mmol/l). The resultant regression was evaluated by the Clarke error grid analysis and all data points fell within the clinically acceptable regions (region A: 93%, region B: 7%). © 2007 IEEE.. | |||||
著者版フラグ | ||||||
出版タイプ | VoR | |||||
出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
関連URI | ||||||
識別子タイプ | DOI | |||||
関連識別子 | http://dx.doi.org/10.1109/IEMBS.2007.4353354 |