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近赤外瞬時差分分光法による非観血的血糖計測のための多変量校正モデルの検討
http://hdl.handle.net/2297/14325
http://hdl.handle.net/2297/14325e40ecfc8-6958-4691-b09c-17d08227538a
名前 / ファイル | ライセンス | アクション |
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TE-PR-YAMAKOSHI-T-49.pdf (1.6 MB)
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Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2017-10-03 | |||||
タイトル | ||||||
タイトル | 近赤外瞬時差分分光法による非観血的血糖計測のための多変量校正モデルの検討 | |||||
タイトル | ||||||
言語 | en | |||||
タイトル | Multivariate Calibration Models for Non-invasive Prediction of Blood Glucose Level Using an Instantaneous Differential Near-infrared Spectrophotometry | |||||
言語 | ||||||
言語 | jpn | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
資源タイプ | journal article | |||||
著者 |
山越, 康弘
× 山越, 康弘× 小川, 充洋× 山越, 健弘× 田村, 俊世× 山越, 憲一 |
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提供者所属 | ||||||
内容記述タイプ | Other | |||||
内容記述 | 金沢大学大学院自然科学研究科 | |||||
書誌情報 |
生体医工学 : 日本エム・イー学会誌 巻 46, 号 1, p. 49-57, 発行日 2008-02-10 |
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ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 1347-443X | |||||
NCID | ||||||
収録物識別子タイプ | NCID | |||||
収録物識別子 | AA11633569 | |||||
出版者 | ||||||
出版者 | 日本生体医工学会 | |||||
抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | An optical method recently proposed for non-invasive in vivo blood glucose concentration (BGL) measurement, named "Pulse Glucometry", was combined and compared with four multivariate analyses for constructing calibration models: Principal Component Regression (PCR), Partial Least Squares Regression (PLS), Artificial Neural Network (ANN), Support Vector Machines Regression (SVMsR). A very fast spectrophotometer for "Pulse Glucometry" provides the total transmitted radiation spectrum (I_λ) and the cardiac-related pulsatile component (ΔI_λ) superimposed on I_λ in human fingertips over a wavelength range from 900 to 1700 nm with resolution of 8 nm in 100 Hz sampling. From a family of I_λs measured, which include information relating to blood constituent such as BGL values, differential optical densities (ΔOD_λs, where ΔOD_λ=Log(1+ΔI_λ/I_λ)) were obtained and normalized by the ΔOD_λ values at 1100 nm. Finally, the 2nd derivatives of the normalized ΔOD_λs(Δ^2OD_λs) along wavelengths were calculated as regressors. Subsequently, calibration models from paired data sets of regressors(the values of Δ^2OD_λs) and regressand (the corresponding known BGL values) were constructed with PCR, PLS, ANN and SVMsR. The results show that each calibration model provides a relatively good regression with a modified 5-fold cross validation for total 95 paired data, in which the BGLs ranged from 100.7-246.3 mg/dl. The results were evaluated by the Clarke error grid analysis and all data points obtained from all calibration models fell within the clinically acceptable regions (region A or B). Among them, ANN and SVMsR calibration provided the best plot distributions (in ANN; Region A: 77 plots (81.1%), B: 18 plots (18.9%). in SVMsR; Region A: 78 (82.1%), B: 17 (17.9%)). Total calculation time of SVMsR is about 100 times shorter than ANN. These results suggest that a calibration model using SVMsR is highly promising for "Pulse Glucometry. | |||||
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 | URI | |||||
関連識別子 | http://ci.nii.ac.jp/naid/110006649735/ |