non-invasive glucose determination in the human eye
TRANSCRIPT
Non-invasive glucose determination in the human eye
Wolfgang Schradera,*, Petra Meuerb, Jurgen Poppc, Wolfgang Kieferb,Johannes-Ulrich Menzebachd, Bernhard Schraderd
aUniversitatsaugenklinik, Universitat Wurzburg, Josef-Schneider-Str. 11, D-97080 Wurzburg, GermanybInstitut fur Physikalische Chemie, Universitat Wurzburg, Am Hubland, D-97074 Wurzburg, Germany
cInstitut fur Physikalische Chemie, Friedrich-Schiller-Universitat Jena, Helmholtzweg 4, D-07743 Jena, GermanydInstitut fur Physikalische und Theoretische Chemie, Universitat Duisburg-Essen, Soniusweg 20, D-45259 Essen, Germany
Received 21 September 2004; revised 16 October 2004; accepted 18 October 2004
Dedicated to Professor Hiroaki Takahashi, Tokyo! One of the authors (B.S.) is grateful for the instruction in 1966 to perform the Normal
Coordinate Analysis of Molecular Crystals and great friendship and scientific cooperation since
Abstract
For non-invasive in vivo glucose determinations by means of near-infrared spectroscopy, the anterior chamber of the human eye is a
promising site. An optical set-up for the non-invasive glucose determination in the human eye precisely in the anterior chamber with a beam
reflected from the surface of the eye lens is presented here. As the anterior chamber has a depth of 3.13G0.50 mm, the beam follows an
optical path of 5.3–7.3 mm depending on the angle of incidence, which is individually constant. We will show that it is possible to acquire
good concentration predictions for physiological glucose concentrations with such a long optical path. A chemometric study of NIR glucose
spectra with concentrations of glucose in water of 10–350 mg/dL (0.56–1.94 mmol/L) resulted in a calibration model which was able to
predict physiological glucose concentrations with a root mean square error of prediction RMSEPTestZ15.41 mg/dL. The Clarke error grid
diagram shows that the model performs well according to medical impact. Using a first in vivo set-up, the precision is not sufficient for a
reliable prediction of glucose concentration, especially due to the flickering of the patient’s eye and the low reflectivity of the eye lens.
Therefore, we have designed a new in vivo set-up: a prototype for a self-monitoring device with controlled geometry and laser radiation at
several distinct wavelengths instead of the halogen lamp as light source. This allows a far higher signal/noise ratio under much better
reproducible geometrical conditions and at the same time a much smaller necessary light flux.
q 2004 Elsevier B.V. All rights reserved.
Keywords: NIR absorption; Aqueous humour; Glucose; Non-invasive determination
1. Introduction
Diabetes mellitus has increasingly become a health threat
in industrialized countries. The prevalence of diabetes
mellitus has doubled within the last 30 years in these
countries to about 5% of the population (in Germany, from
two to four million people) [1]. As shown by the diabetes
control and complications trial (DCCT), late complications
occur less frequently in patients who adjust their insulin
0022-2860/$ - see front matter q 2004 Elsevier B.V. All rights reserved.
doi:10.1016/j.molstruc.2004.10.115
* Corresponding author. Tel.: C49 931 20120610; fax: C49 931
20120490.
E-mail address: [email protected]
(W. Schrader).
intake to their eating behaviour with multiple injections
rather than keep a strict diet with only two injections per day
[2]. Therefore, diabetic patients have to rely on frequent
blood glucose measurements to control their blood glucose
levels.
Most diabetics use a self-monitoring device, which
works with a small droplet of blood drawn from the
fingertip. This can turn out to be quite painful in the long
run, and even lead to severe sensitivity loss of the fingertips.
To ensure a high patient compliance with this therapy
scheme, the glucose determinations should be as painless
and convenient for the patient as possible.
Therefore, various approaches for minimal and non-
invasive determination have been suggested [3].
Journal of Molecular Structure 735–736 (2005) 299–306
www.elsevier.com/locate/molstruc
W. Schrader et al. / Journal of Molecular Structure 735–736 (2005) 299–306300
Non-invasive measurement sites on the human body have to
fulfill certain criteria [4]. The site should be easily
accessible at least with a quartz fibre, it should be
temperature stable or temperature controllable, it has to
contain glucose in measurable concentrations, and the
glucose concentration at that site has to have a constant
relation towards that in the blood.
Specific studies have demonstrated that NIR spec-
troscopy represents a promising tool for the non-invasive
prediction of blood glucose concentration. Diffuse reflection
measurements were performed by Robinson et al. [5] at the
finger with different instrument configurations, by Marbach
et al. [6] and Heise et al. [7] of the oral muscosa, by
Fischbacher et al. [8], Danzer et al. [9] and Muller et al. [10]
on the middle finger of the right hand and by Malin et al.
[11] on the forearm. Burmeister et al. [12] collected
transmission spectra through the tongue. Another method
for non-invasive glucose determination is the combination
of photoacoustic spectroscopy with modulated laser diodes
in aqueous solutions as reported by Spanner et al. [13].
In all these studies, limitations were cited that affect the
reliability of the method. These limitations included
sensitivity, sampling problems, time lag, calibration bias,
long-term reproducibility, and instrument noise, as well as
the fact that glucose concentrations in these body regions
are very low compared to the ones in blood [3].
Additionally, accurate non-invasive estimation of blood
glucose is limited at present by the dynamic nature of the so
far used sample sites: the skin and living tissue of the patient
[14]. Chemical, structural, and physiological variations
occur that produce dramatic changes in the optical proper-
ties of the tissue sample. Temperature variations are another
obstacle, as NIR spectra are very sensitive towards
temperature changes especially when dealing with aqueous
matrices [15]. The measurement is further complicated by
the varying background signals of other substances present
in the blood or tissue, e.g. body fat and proteins. The
analysis of in vivo spectra is quite complex as the spectra
exhibit very broad, overlapping bands.
Another possible sample location, which has not been
extensively investigated so far, is the eye. Wickstedt et al.
[16] and Borchert et al. [17] reported on Raman spectro-
scopic measurements of rabbit aqueous humour. Backhaus
et al. [18,19], Menzebach [20] and Schrader et al. [21,22]
proposed in vivo NIR transmission measurements of the
aqueous humour, where the light is reflected at the front of
the eye lens. Additionally Menzebach [20] discussed
different techniques for the realization of glucose concen-
tration measurement in the human eye, e.g. the use of optical
rotation. This has also been investigated by Cameron and
Cote [23] and Cameron et al. [24].
The aqueous humour is a liquid, which fills the anterior
chamber of the human eye. This chamber is located between
the cornea and the lens with a depth of 3.13G0.50 mm. [25].
It can be easily reached by spectroscopic means—in the
wavelength range where the cornea is transparent. Due to its
location in the orbital, it is well temperature stabilized, even
more so as the cornea with its tear film regulates the
temperature of the eye. The aqueous humour is a kind of
ultra filtrate of the human blood, and is responsible for
controlling the intra-ocular pressure and the nourishment of
the lens, as well as removing the intermediate catabolic
products from the cornea [26]. It contains glucose in
concentrations of 65–85 mg/dL (3.6–4.8 mmol/L), corre-
sponding to about 63–76% of the glucose content in the
blood [27,28].
A glucose determination in the aqueous humour is
possible when some requirements are fulfilled. The optical
path has to have an intra-individually reproducible length
and has to allow an easy non-invasive measurement.
Cameron et al. suggested a path for polarimetry measure-
ments in the anterior chamber that requires contact to the
cornea and therefore anaesthesia [24]. The path under
investigation here uses the third of the Purkinje–Sanson
images [29]. The four Purkinje–Sanson images are pro-
duced by reflections from the front and back of the cornea
and the lens (see Fig. 6).
By focusing on the reflection on the front of the eye lens,
the returning light travels twice through the anterior
chamber thus covering a distance of about 7 mm at an
angle of about 458 from the normal. For the in vitro
experiments, a 5 mm cell is used [30].
Near-infrared spectra are not very expressive for aqueous
solutions with small glucose concentrations as the spectra
are dominated by water absorption. However, an analysis
can be performed with the use of multivariate procedures.
To establish a valid chemometric model for the in vivo
determination of glucose in the aqueous humour, we
developed an in vitro calibration model and present an
experimental set-up for the in vivo non-invasive determi-
nation of glucose.
2. Material and methods
D(C)-Glucose for biochemistry (MERCK) was used
without further purification. Each glucose sample was
weighed separately to achieve stochastic independence of
the samples. The samples were dissolved in highly purified
water and conserved by adding 0.05% NaN3. All samples
were prepared freshly each day. Prior to the measurement,
the samples were thermostated at about 36 8C. The reference
concentrations were measured with the hexokinase method
on a Hitachi 911 analyser from Roche (instrument precision
G0.5% within a day).
The near-infrared spectra were recorded with a Vector
22/N-C interferometer system from Bruker (Germany) with
a Peltier-cooled InGaAs detector. The detector (D 427/N,
Bruker, Germany) covers a range between 4000 and
12,800 cmK1 and has a noise equivalent power NEP of !2!10K13 W/HzK1/2. The data were collected between
4000 and 12,500 cmK1 with a spectral resolution of
Fig. 1. Typical near-infrared spectra of aqueous glucose solutions with
concentrations in the physiological range between 10 and 350 mg/dL
(0.56–1.94 mmol/L). Only the regions 5377.2–6542.1 cmK1 and 7170.9–
11001.2 cmK1 showed a sufficient signal/noise ratio and were used for the
PLS regression.
W. Schrader et al. / Journal of Molecular Structure 735–736 (2005) 299–306 301
8 cmK1. The interferograms were collected double-sided
forward–backward.
All samples were measured in a Suprasil thermo cell
(Hellma, Germany) with a fixed path length of 5 mm. This
cell has a water-cooled jacket, which was attached to a
thermostat (MV-4, Julabo). The temperature in the sample
cell was controlled at 37.0 8C (G0.1 8C). Prior to the
measurements, the solution in the sample cell was checked
for air bubbles, which were removed if present.
Each spectrum collected was obtained as an average of
100 scans/sample with a total scan time of 60 s. Two sets of
35 samples each were prepared with varying concentrations,
ranging from 10 to 350 mg/dL (0.56–1.94 mmol/L) in
10 mg/dL steps.
Fig. 2. Differential spectra of aqua bidest (thickness of 1 mm) under various temp
were taken with a Perkin–Elmer Lambda 9 Spectrometer.
The chemometric analysis was performed as described in
the dissertation of Meuer [31] with the program package
QUANT from OPUS (Bruker, Germany) [32] using the
implemented PLS-1 algorithm and in-house developed
routines for Matlab (The Mathworks, Natick MA, USA)
[33,34]. To put the results into a medical context, the
concentration correlations are plotted in a Clarke error grid
produced with the BD Error Grid.xls program [35].
3. Results and discussion
3.1. In vitro glucose determination with 5 mm optical path
Near-infrared absorption spectra of aqueous glucose
solution (see Fig. 1) are dominated by water, and show very
little variation between different concentrations in the
physiological range.
NIR spectra of water exhibit four bands in the NIR region
[36,37], which are combinations of the fundamental
vibrations: the symmetric stretching mode n1 (ns) at
3615 cmK1, the antisymmetric stretching mode n3 (na) at
3450 cmK1 and the bending mode n2 (d) at 1640 cmK1. In the
NIR these give rise to the combination mode n1Cn3 around
7040 cmK1 (1420 nm), the n1Cn2Cn3 around 8620 cmK1
(1160 nm) and around 10,340 cmK1 (967.1 nm) the 2n1Cn3
combination mode. The combination mode n2Cn3 around
5260 cmK1 (1901 nm) is not observed due to the high sample
thickness of 5 mm, which leads to a cut off lower than
5350 cmK1 (1869 nm). The same applies to the combination
mode n1Cn3 around 7040 cmK1 (1420 nm). The position
and width of OH-vibrations are usually [40] strongly
temperature-dependent. This is shown in Fig. 2, where the
absorption spectrum of water at temperatures 32–38 8C is
recorded relative to that at 40 8C.
The spectra show isosbestic points—where the tempera-
ture-dependence is zero. They may be used as fixed points to
eratures. As a reference, the water spectrum at 40 8C was chosen. Samples
Table 1
Isosbestic points of the NIR absorption spectrum of water, with no
temperature dependence in the NIR spectrum
cmK1 nm
8770 1140
8396 1191
7655 1305
6944 1440
5591 1790
4590 2180
W. Schrader et al. / Journal of Molecular Structure 735–736 (2005) 299–306302
determine the sample thickness, and are compiled in
Table 1.
The absorption spectrum of glucose relative to water is
shown in Fig. 3. There is a combination of the IR bands of
glucose at 3310 and 1457 cmK1 (4767 cmK1), appearing at
2120 nm, further, another combination of the IR bands at
2945 and 1457 cmK1 appearing at 2260 nm. At 1690 nm,
there is the first overtone of the IR band at 2945 cmK1, a CH
stretching vibration. Since it is less dependent on tempera-
ture changes than an OH stretching modes, Hazen et al. [15]
recommended this band as useful for glucose determination.
Finally, there is at 1560 nm the overtone of a OH-stretching
vibration at 3310 cmK1. In order to see the bands due to
glucose in the diagram, the concentration of the solutions
giving the spectra is much higher (1–10%) than the
physiological one (in the order of 0.1%).
Classical univariate calibration of glucose in water is
impossible, since we found no wavenumber where sufficient
selectivity for glucose exists. Hence, multivariate cali-
bration techniques need to be applied.
Two spectral regions, 5377.2–6542.1 cmK1, and 7170.9–
11001.2 cmK1 (see Fig. 1), showing an absorbance lower
than three absorbance units were selected for partial least
squares (PLS) regression.
Fig. 3. Absorption spectra of glucose in aqua bidest at various concentrations rela
Samples were taken with a Perkin–Elmer Lambda 9 Spectrometer.
A plot of the experimental versus the predicted values is
shown in Fig. 4. The minimum cross-validated root mean
squared error of prediction (RMSEPCV) was attained at 11
PLS factors and resulted in a cross-validated R2 of 97.87%
and a RMSEPCV of 14.44 mg/dL. The 11 factors cannot be
assigned to physical parameters. The system’s variable
parameters shift the broad unseparated NIR bands, and thus
have non-linear effects on the spectral channels. Details are
described in Ref. [31].
To determine the medical impact for in vivo glucose
measurements, the results were plotted in a Clarke error grid
[38,39] in Fig. 5. This error grid analysis offers a quick
estimation of the medical accuracy of the measurement.
Data from the test device are plotted against the results of a
reference method. A scatter diagram is established and
divided into five zones [38,39]. The five zones A–E show
varying degrees of accuracy of glucose estimation, which
correlates with an adequate or inadequate treatment.
Explicitly, zone A: no effect on clinical action; B: altered
clinical action of little or no effect on clinical outcome; C:
altered clinical action—likely to effect clinical outcome; D:
altered clinical action—could have significant medical risk;
E: altered clinical action—could have dangerous
consequences.
With one exception, all data points fall in zone A and
only one prediction is located in zone B. The calibration
model used for the prediction of the data performs well, and
the predictions result in medically uncritical deviations.
3.2. Experimental set-up for the non-invasive in vivo
determination of glucose
For a non-invasive in vivo glucose determination in the
eye, a suitable experimental set-up is needed. It uses a path
through the anterior chamber of the human eye with an
tive to the spectrum of water. The temperature was kept constant at 37 8C.
Fig. 4. Glucose concentration correlation plot of experimental versus
predicted glucose concentrations for the 131 spectra of the training set. The
regression was performed in the spectral ranges from 5377.2 to 6542.1 cmK1
and 7170.9 to 11001.2 cmK1.
Fig. 6. Positions of the four Purkinje–Sanson images relative to the incident
light. L light source, 1: reflection from the front of the cornea, 2: reflection
from the back of the cornea, 3: reflection from the front of the lens, 4:
reflection from the back of the lens.
W. Schrader et al. / Journal of Molecular Structure 735–736 (2005) 299–306 303
intra-individually constant length using the reflection
according to the third Purkinje–Sanson image. Light
reflected there travels twice through the anterior chamber
covering an individually constant length of about 6–7 mm,
and can be used to obtain transmission spectra of the
aqueous humour. A sideways cut through the human eye
and the positions of the four Purkinje–Sanson images are
shown in Fig. 6.
Fig. 5. Clark error grid diagram of the correlation of true versus calculated
glucose concentrations for the 66 spectra of the set with ‘unknown’ samples.
Zone A: no effect on clinical action, B: altered clinical action or little or no
effect on clinical outcome, C: altered clinical action—likely to affect
clinical outcome, D: altered clinical action—could have significant medical
risk, E: altered clinical action—could have dangerous consequences. The
diagram was produced with the BD Error Grid.Xls program [35].
In vivo near-infrared spectra are recorded with a set-up
illustrated in Fig. 7(A) on a Vector 22/N-C interferometer
(Bruker, Germany) equipped with an InGaAs detector. The
spectrometer is modified to allow the connection to a quartz
fibre. The internal light source of the interferometer is
switched off. The connecting quartz fibre has a diameter of
1 mm and a length of 2 m (Optran WF 1000/1100 N,
CeramOptec, Germany). The external light source is an air-
cooled tungsten lamp (12 V/30 W, model 64261, Osram,
Germany) running with a stabilized current of 2.5 A. The in
vivo optics in front of the eye consists of four plane-convex
quartz lenses and two variable iris diaphragms (Spindler &
Hoyer, Germany). The quartz fibre is mounted in the image
plane of a reflex camera (OM-1, Olympus, Germany) to
allow a visual control of the focus plane. Additionally, two
optical filters were used: a RG 665 1.0 (Schott, Germany)
between the light source and the eye to limit the light range
reaching the eye and a RG 850 1.0 (Schott, Germany) right
in front of the quartz fibre to suppress stray light from the
visible range reaching the spectrometer. This set-up was
optimised using a ray tracing program of OpticsLab
(Science Lab Software, Carlsbad, CA).
The spot size of the light beam for illumination and
observation are regulated with variable iris diaphragms.
The focus is directed by the observer. The observer, who
is used to slit lamp examinations, adjusts the third Purkinje–
Sanson image to the centre of the camera image.
The camera is focused onto the lens surface, where the
third Purkinje–Sanson image is reflected. The light reflected
from the lens is then collected with another two plane-
convex quartz lenses, and directed into a quartz fibre with a
diameter of 1 mm. The end of the quartz fibre is mounted in
the image plane of the reflex camera. This set-up allows
the observer to focus the light exactly into the third
Fig. 7. (A) Ray tracing of the set-up for non-invasive measurements in the human eye. (B) Typical in vivo spectrum of the human eye collected with the
described set-up (light source 2.5 A, 12 V, with absorption filters Schott RG 665 1.0, RG 850 1.0 (not shown in the tracing diagram, resolution 8 cmK1,
32 scans).
W. Schrader et al. / Journal of Molecular Structure 735–736 (2005) 299–306304
Purkinje-Spot when the mirror is down, and to take spectra
with the mirror up.
Fig. 8 shows the result of an in vivo measurement of the
glucose concentration with an arrangement as seen in
Fig. 7(A). The diagram proves that the glucose concen-
tration can be measured with an arrangement such as
Fig. 7(A). However, the mean deviation of glucose
concentration in the eye—optically measured—and that of
the blood analysis is 28 mg/dL equivalent to about 21%.
Fig. 8. Glucose concentrations in the capillary blood and in the aqueous humour of
authors, B.S.). Values in the aqueous humour follow the blood values with a late
This is somewhat high as regards the requirements of a
reliable measurement, and is due to:
1.
the
ncy
the head holder did allow movements of the patient, and
the observer had to adjust for them during each
measurement individually, making it difficult to measure
exactly at the geometrically optimal arrangement and
2.
the reflectance of the front surface of the eye lens is onlyabout 0.1%.
eye during an oral glucose tolerance test in a human subject (one of the
of about 20 min. Spectra were analysed with PCR and PRESS.
W. Schrader et al. / Journal of Molecular Structure 735–736 (2005) 299–306 305
Both effects can be compensated for as shown in the next
paragraph.
We plan to improve the set-up to make a self-monitoring
device possible. The tungsten lamp light source L in Fig. 6
will be replaced by a set of lasers, emitting at wavelengths at
suitable positions of the glucose and water spectrum:
maxima and minima as well as at isosbestic points
(Table 1). A monitor detector measuring the intensity of
the beams 1 and 2 in Fig. 6 allows the measurement at
position 3 only, when the measuring beam is optimally
adjusted. An acoustical signal will help the patient to find
this optimal beam. Having a set of lasers with spectrally
very sharp lines instead of the continuous spectrum of the
halogen lamp allows a much higher signal/noise ratio of
the signals together with much smaller light flux used for the
measurement [22,41].
4. Conclusions and outlook
It has been shown that physiological concentrations of
glucose in water can be determined from NIR spectra
collected with 5 mm optical path length. The correlation
between experimental and predicted values indicate that the
models are based on glucose specific spectral information,
and that these models are potentially reliable over time.
A suitable set-up for the in vivo non-invasive NIR
measurement of glucose in the human eye is presented.
Using this set-up, the first in vivo spectra were acquired and
the glucose concentrations determined. Even though the
medically desired prediction error of less than 10 mg/dL has
not yet been reached, the results are very promising, and
show the feasibility of in vivo determination of glucose in
the human eye. A way to improve the quality of this set-up
and to construct a self-monitoring apparatus for a diabetic
patient is described.
Acknowledgements
Support from the Erweiterte Forschungsforderung der
Universitat Wurzburg, Grant 2c/1998, and the Deutsche
Forschungsgemeinschaft, DFG Grant Schr 598/2-1, is
highly acknowledged. J. Popp highly acknowledges the
support from the Freistaat Bayern (Bayerisches Habilita-
tionsstipendium) and W. Kiefer acknowledges financial
support from the Fonds der Chemischen Industrie.
References
[1] H.U. Janka, D. Michaelis, Z. Arztl. Fortbild. Qualitaetssich 96 (2002)
159.
[2] The diabetes control and complications trial research group, JAMA
276 (1996) 1409.
[3] J. Pickup, L. McCartney, O. Rolinski, D. Birch, Br. Med. J. 319 (1999)
1289.
[4] P.G. Steffes, Diabetes Technol. Ther. 1 (1999) 129.
[5] M.R. Robinson, R.P. Eaton, D.M. Haaland, G.W. Koepp,
E.V. Thomas, B.R. Stallard, P.L. Robinson, Clin. Chem. 38 (1992)
1618.
[6] R. Marbach, T. Koshinsky, F.A. Gries, H.M. Heise, Appl. Spectrosc.
47 (1993) 874.
[7] H.M. Heise, R. Marbach, T. Koschinsky, F.A. Gries, Artif. Organs 18
(1994) 439.
[8] C. Fischbacher, K.-U. Jagemann, K. Danzer, U.A. Muller,
L. Papenkordt, J. Schuler, Fresenius J. Anal. Chem. 359 (1997) 78.
[9] K. Danzer, C. Fischbacher, K.U. Jagemann, K.J. Reichelt, LEOS
Newslett. 1988 (1998) 9.
[10] U.A. Muller, B. Mertes, C. Fischbacher, K.U. Jageman, K. Danzer,
Int. J. Artif. Organs 20 (1997) 285.
[11] S.F. Malin, T.L. Ruchti, T.B. Blank, S.N. Thennadil, S.L. Monfre,
Clin. Chem. 45 (1999) 1651.
[12] J.J. Burmeister, M.A. Arnold, G.W. Small, Diabetes Technol. Ther. 2
(2000) 5.
[13] G. Spanner, R. Niesner, Fresenius J. Anal. Chem. 354 (1996) 306.
[14] O.S. Khalil, Clin. Chem. 45 (1999) 165.
[15] K.H. Hazen, M.A. Arnold, G.W. Small, Appl. Spectrosc. 48 (1994)
477.
[16] J.P. Wicksted, R.J. Erkens, M. Motamedi, W.F. March, Appl.
Spectrosc. 49 (1995) 987.
[17] M.S. Borchert, M.C. Storrie-Lombardi, J.L. Lambert, Diabetes Tech.
Ther. 1 (1999) 145.
[18] J. Backhaus, D. Bocker, B. Schrader, W. Schrader, H.U. Menzebach,
E. Schmidt, Vorrichtung zur in vivo Bestimmung einer optischen
Eigenschaft des Kammerwassers des Auges, European Patent Nr.
93119838, Feb 24 1999.
[19] J. Backhaus, D. Bocker, B. Schrader, W. Schrader, H.U. Menzebach,
E. Schmidt, Device for the in vivo determination of an optical
property of the aqueous humor of the eye, US Patent 5535743, Jul 16
1996.
[20] J.U. Menzebach, Nichtinvasive Diagnostik mit Hilfe der Bestimmung
optischer Eigenschaften der Augenvorderkammerfluessigkeit, Bes-
timmung der Blutglucose beim Diabetiker, Dissertation Universitat
Essen, Essen, 1996.
[21] W.F. Schrader, Invest. Ophthalmol. Vis. Sci. 39/4 (1998) S926.
[22] B. Schrader, W. Schrader, Verfahren und Vorrichtung zur auto-
matischen Messung der Konzentration von Komponenten des
Augenvorderkammerwassers sowie Verwendung derselben,
Deutsches Patent Nr. 19830541, Jun 22 2004.
[23] B.D. Cameron, G.L. Cote, IEEE Trans. Biomed. Eng. 44 (1997) 1221.
[24] B.D. Cameron, H.W. Gorde, B.E. Satheesan, G.L. Cote, Diabetes
Tech. Ther. 1 (1999) 135.
[25] W. Haigis, Biometrie bei komplizierten Ausgangssituationen. In 9.
Kongr. d. Deutsch. Ges. f. Intraokularlinsen Implant, Springer Verlag,
Berlin, 1996. p. 17.
[26] R. Moses, Adler’s Physiology of the Eye, 8th ed., Mosby Company,
Saint Louis, 1987.
[27] S. Pohjola, Acta Ophthalmologica Suppl. 88 (1966) 1.
[28] W.F. Schrader, R. Grajewski, P. Meuer, Invest. Ophthalmol. Vis. Sci.
41 (2000) 77.
[29] H. Helmholtz, Handbuch der physiologischen Optik (Allgemeine
Enzyklopadie der Physik Bd. 9), Leipzig, 1867.
[30] K.H. Hazen, M. Arnold, G.W. Small, Appl. Spectrosc. 52 (1998)
1597.
[31] P. Meuer, Spektroskopische Untersuchungen an Kammerwasser: in
vitro und in vivo, Thesis, Julius-Maximillians-University, Wurzburg,
2003.
[32] Bruker Analytik GmbH, Multivariate Kalibration: Ein praktischer
Leitfaden zur Methodenentwicklung in der quantitativen Analytik,
Ettlingen, 1998.
W. Schrader et al. / Journal of Molecular Structure 735–736 (2005) 299–306306
[33] K. Baumann, H. Albert, M.v. Korff, J. Chemometrics 16 (2002)
339.
[34] K. Baumann, H. Albert, M.v. Korff, J. Chemometrics 16 (2002) 351.
[35] The BD Consumer Health Care Error Grid (13th Febr 2002), fttp
BDCHC.com, 2002.
[36] K. Buijs, G.R.J. Choppin, Chem. Phys. 39 (1963) 2035.
[37] G.R.J. Choppin, J.R.J. Downey, J. Chem. Phys. 56 (1972) 5899.
[38] W.I. Clarke, D. Cox, L.A. Gonder-Frederick, W. Carter, S.L. Pohl,
Diabetes Care 10 (1987) 622.
[39] J.L. Parkes, S.L. Slatin, S. Pardo, B.H. Ginsberg, Diabetes Care 2000; 23.
[40] Infrared and Raman Spectroscopy, in: B. Schrader (Ed.),, VCH,
Weinheim, 1995.
[41] M.N. Ediger, R.J. Landry, D.H. Sliney, Diabetes Technol. Ther. 1
(1999) 239.