Noninvasive blood glucose sensing on human body with near-infrared reflection spectroscopy

2011 ◽  
Author(s):  
Zhen-hao Huang ◽  
Chang-ning Hao ◽  
Lin-lin Zhang ◽  
Yan-chao Huang ◽  
Yi-qin Shi ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Human Body ◽  
Near Infrared ◽  
Glucose Sensing ◽  
Reflection Spectroscopy ◽  
Infrared Reflection ◽  
Infrared Reflection Spectroscopy

Non-Invasive Blood Glucose Monitoring by Means of near Infrared Spectroscopy: Methods for Improving the Reliability of the Calibration Models

1997 ◽  
Vol 20 (5) ◽  
pp. 285-290 ◽  
Author(s):  
U.A. Müller ◽  
B. Mertes ◽  
C. Fischbacher ◽  
K.U. Jageman ◽  
K. Danzer
Keyword(s):  
Blood Glucose ◽  
Near Infrared ◽  
Glucose Monitoring ◽  
Blood Glucose Monitoring ◽  
Least Squares Regression ◽  
Non Invasive ◽  
Infrared Reflection ◽  
Calibration Models ◽  
Infrared Reflection Spectroscopy

The feasibility of using near infrared reflection spectroscopy for non-invasive blood glucose monitoring is discussed. Spectra were obtained using a diode-array spectrometer with a fiberoptic measuring head with a wavelength ranging from 800 nm to 1350 nm. Calibration was performed using partial least-squares regression and radial basis function networks. The results of different methods used to evaluate the quality of the recorded spectra in order to improve the reliability of the calibration models, are presented.

Fourier Transform Near Infrared Spectroscopy Analysis of Power Plant Coal Quality

2011 ◽  
Vol 236-238 ◽  
pp. 799-803 ◽  
Author(s):  
Shuai Wang ◽  
Xin Lu Feng ◽  
Jun Zhou ◽  
Xue Mei Wang
Keyword(s):  
Energy Source ◽  
Near Infrared ◽  
Calorific Value ◽  
Measuring Instruments ◽  
Reflection Spectroscopy ◽  
Quality Of Data ◽  
Near Infrared Spectra ◽  
Infrared Reflection ◽  
Noisy Signals ◽  
Infrared Reflection Spectroscopy

Studied the correlation of near-infrared spectra data and six coal indices, found ash and calorific value has low correlations with spectra data; then use dynamic principal components PLS method predict the coal index; this method could predict Volatile and Hydrogen content better, however, the ability to predict Carbon content and Nitrogen content is lower. It is found that using reflection spectroscopy analyzes the coal need a strong energy source, because the color of coal is deep and reflection is very weak, this leads to noisy signals. Only by improving the energy source could solve the problem of poor spectra data fundamentally; spectral data mining cannot fundamentally improve the quality of data. The current near-infrared reflection spectroscopy common platform such as BRUKER is not suitable for coal analysis, analysis of coal to be better need to develop special near-infrared measuring instruments.

Process Control in Ultraviolet Curing with in-line near Infrared Reflection Spectroscopy

2008 ◽  
Vol 16 (3) ◽  
pp. 165-171 ◽  
Author(s):  
Tom Scherzer ◽  
Katja Heymann ◽  
Gabriele Mirschel ◽  
Michael R. Buchmeiser
Keyword(s):  
Process Control ◽  
Near Infrared ◽  
Reflection Spectroscopy ◽  
Ultraviolet Curing ◽  
Infrared Reflection ◽  
Infrared Reflection Spectroscopy
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