37 6 2004 6 Journal of Tianjin University Vol. 37 No. 6 Jun. 2004 Ξ 1,2, 1,2, 3 (1., 300072 ; 2. 2, 300072 ; 3., 300072) :,,,.,,(RMSEP) 53 %58 %.. : ; ; : O657. 33 : A : 04932 2137 (2004) 062 05352 05 Application of Wavelet Transform in Fundamental Study of Measurement of Blood Glucose Concentration with Near2Infrared Spectroscopy LIU Ze2yi 1,2, TANG Guo2xin 1,2, XU Ke2xin 3 (1. School of Science, Tianjin University,Tianjin 300072,China ; 2. Liu Hui Center for Applied Mathematics, Nankai University & Tianjin University,Tianjin 300072,China ; 3. National Key Lab of Precision Measuring & Testing Techniques and Instruments, Tianjin University,Tianjin 300072,China) Abstract: Because of its properties of time2frequency transform, the wavelet transform is an effective denoised method. With the pretreatment of spectra based on wavelet analysis, the spectra2to2noise ratio was greatly improved while the noise was suppressed effectively. It also improved the prediction precision and robust of the model. This method is applied to fundamental study of measurement of blood glucose concentration with spectroscopy. Experimen2 tal results show that the Root mean square error of prediction (RMSEP) of the calibration model reduces by 53 % and 58 % respectively. It is instructive for the study of the theory of measurement of blood glucose with spectroscopy. Keywords : wavelet transform; human blood glucose concentration ; robust,..,,. [1,2 ].,,.,,.,,. Ξ :20032 032 13 ; :20032 082 31. : (30170261) ;(BA706B221) ;; 2. :(1958 ),,,.
536 37 6, [39 ],. 1 1. 1,. 1),,,,,.,,,. 2) (),.,.,,.. 3).,,, ;,, ;,,,,,. 1. 2,,.,,. :,; ;,. : s ( i) = f ( i) + e ( i), i = 0, 1,, n - 1., f ( i) ; e ( i ) ; s ( i ). 3 : 1), N,s ( i) N ; 2),, 1 N ; 3), N 1 N,., :,,;, ;,,.,.,,,. 1. 3,,.,,,.,,,,.,,,,.,, 12 1. 1 2,,,.,
2004 6 : 537.,,,.,,. 1 Tab. 1 Results comparison of the pretreatments RMSEP/ (mg dl - 1 ) Savitzky2Golay 0. 995 1 8. 337 0 0. 995 8 7. 852 2 0. 997 2 6. 797 4 2 2. 1 Perkin2Elmer Spectrum GX, InSb, 2 70015 000 cm - 1, 1 cm - 1,1 mm,, TBA30.,, TBD,. 2. 2 : 100 ml, 100 ml ;, 1 500,10 min ;,TBA30. 2. 3 50, 10 500 mg/ dl,, 146. 9 mg/ dl ( 33 ),0 1 000 mg/ dl,0360 mg/ dl, ;36, 205. 2718. 2 mg/ dl,, 140. 2 mg/ dl.
538 37 6 3 3. 1 4 300 cm - 1 4 400 cm - 1 4 700 cm - 1 3 ;3 800 cm - 1 5 200 cm - 1,4 500 cm - 1,, 4 2004 800 cm - 1. 3. 2 db2, 3., N 1 N.,,. 2 2 PLS ( ), RMSEP. :,. 2 RMSEP RMSEP 47 %42 %. 2,2 2,. 3,, 2., RMSEP 27. 5 mg/ dl 19. 55 mg/ dl, RMSEP 5. 84 mg/ dl 3. 603 7 mg/ dl. 3 4,,,. 2 Tab. 2 Prediction results of the model without wavelet transform RMSEP/ (mg/ dl) RMSEP/ (mg/ dl) ( ) 11 37. 678 0. 965 3 7. 208 0. 560 11 41. 396 0. 971 3 8. 619 0. 193 (a) 1 ( ) 9 28. 264 0. 981 3 6. 951 0. 624 9 19. 116 0. 993 3 5. 861 0. 624 2 ( ) 8 27. 501 0. 982 3 5. 842 0. 779 8 19. 550 0. 992 3 3. 604 0. 949 3 ( ) 8 30. 135 0. 978 3 6. 507 0. 676 8 20. 476 0. 991 3 5. 849 0. 628 (b) 3 Fig. 3 Prediction results of four components sample
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