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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
著者: Ogawa, Mitsuhiro
Yamakoshi, Yasuhiro
Satoh, Makoto
Nogawa, Masamichi link image link image
Yamakoshi, Takehiro
Tanaka, Shinobu link image link image
Rolfe, Peter
Tamura, Toshiyo
Yamakoshi, Ken-ichi
佐藤, 純
野川, 雅道
山越, 健弘
田中, 志信
山越, 憲一
発行日: 2007年
出版社(者): Institute of Electrical and Electronics Engineers (IEEE)
雑誌名: Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
ISSN: 0589-1019
号: 4353354
開始ページ: 4561
終了ページ: 4563
抄録: 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..
DOI: 10.1109/IEMBS.2007.4353354
URI: http://hdl.handle.net/2297/14390
関連URI: http://dx.doi.org/10.1109/IEMBS.2007.4353354
資料種別: Conference Paper
版表示: publisher
出現コレクション:1.査読済論文(工)

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