TY - JOUR
T1 - Fiber-optic evanescent-wave spectroscopy for fast multicomponent analysis of human blood
AU - Simhi, Ronit
AU - Gotshal, Yaron
AU - Bunimovich, David
AU - Sela, Ben Ami
AU - Katzir, Abraham
PY - 1996/7/1
Y1 - 1996/7/1
N2 - A spectral analysis of human blood serum was undertaken by fiber-optic evanescent-wave spectroscopy (FEWS) by the use of a Fourier-transform infrared spectrometer. A special cell for the FEWS measurements was designed and built that incorporates an IR-transmitting silver halide fiber and a means for introducing the blood-serum sample. Further improvements in analysis were obtained by the adoption of multivariate calibration techniques that are already used in clinical chemistry. The partial least-squares algorithm was used to calculate the concentrations of cholesterol, total protein, urea, and uric acid in human blood serum. The estimated prediction errors obtained 1in percent from the average value2 were 6% for total protein, 15% for cholesterol, 30% for urea, and 30% for uric acid. These results were compared with another independent prediction method that used a neural-network model. This model yielded estimated prediction errors of 8.8% for total protein, 25% for cholesterol, and 21% for uric acid.
AB - A spectral analysis of human blood serum was undertaken by fiber-optic evanescent-wave spectroscopy (FEWS) by the use of a Fourier-transform infrared spectrometer. A special cell for the FEWS measurements was designed and built that incorporates an IR-transmitting silver halide fiber and a means for introducing the blood-serum sample. Further improvements in analysis were obtained by the adoption of multivariate calibration techniques that are already used in clinical chemistry. The partial least-squares algorithm was used to calculate the concentrations of cholesterol, total protein, urea, and uric acid in human blood serum. The estimated prediction errors obtained 1in percent from the average value2 were 6% for total protein, 15% for cholesterol, 30% for urea, and 30% for uric acid. These results were compared with another independent prediction method that used a neural-network model. This model yielded estimated prediction errors of 8.8% for total protein, 25% for cholesterol, and 21% for uric acid.
KW - Attenuated total-reflection spectroscopy
KW - Blood
KW - Fiber-optic evanescent-wave spectroscopy
KW - Fourier-transform infrared spectrometer
KW - Multivariate calibration
KW - Neural networks
UR - http://www.scopus.com/inward/record.url?scp=0000044034&partnerID=8YFLogxK
U2 - 10.1364/AO.35.003421
DO - 10.1364/AO.35.003421
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AN - SCOPUS:0000044034
SN - 1559-128X
VL - 35
SP - 3421
EP - 3425
JO - Applied Optics
JF - Applied Optics
IS - 19
ER -