CA2418399A1 - Non-invasive system for the determination of analytes in body fluids - Google Patents

Non-invasive system for the determination of analytes in body fluids Download PDF

Info

Publication number
CA2418399A1
CA2418399A1 CA002418399A CA2418399A CA2418399A1 CA 2418399 A1 CA2418399 A1 CA 2418399A1 CA 002418399 A CA002418399 A CA 002418399A CA 2418399 A CA2418399 A CA 2418399A CA 2418399 A1 CA2418399 A1 CA 2418399A1
Authority
CA
Canada
Prior art keywords
body tissue
light
infrared light
glucose
fluid
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Abandoned
Application number
CA002418399A
Other languages
French (fr)
Inventor
Mihailo V. Rebec
James E. Smous
Steven D. Brown
Hu-Wei Tan
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Bayer Healthcare LLC
Original Assignee
Bayer Healthcare LLC
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Bayer Healthcare LLC filed Critical Bayer Healthcare LLC
Publication of CA2418399A1 publication Critical patent/CA2418399A1/en
Abandoned legal-status Critical Current

Links

Classifications

    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/145Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
    • A61B5/14532Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue for measuring glucose, e.g. by tissue impedance measurement
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/145Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
    • A61B5/1455Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue using optical sensors, e.g. spectral photometrical oximeters
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/145Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
    • A61B5/1495Calibrating or testing of in-vivo probes
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/31Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
    • G01N21/35Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
    • G01N21/359Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235Details of waveform analysis
    • A61B5/7253Details of waveform analysis characterised by using transforms
    • A61B5/726Details of waveform analysis characterised by using transforms using Wavelet transforms
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/27Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands using photo-electric detection ; circuits for computing concentration
    • G01N21/274Calibration, base line adjustment, drift correction
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2201/00Features of devices classified in G01N21/00
    • G01N2201/06Illumination; Optics
    • G01N2201/067Electro-optic, magneto-optic, acousto-optic elements

Abstract

A system for determining the concentration of an analyte in at least one body fluid in body tissue, the system compris-ing an infrared light source, a body tissue interface, a de-tector, and a central processing unit. The body tissue inter-face is adapted to contact body tissue and to deliver light from the infrared light source to the contacted body tissue.
The detector is adapted to receive spectral information corre-sponding to infrared light transmitted through the portion of body tissue being analyzed and to convert the received spec-tral information into an electrical signal indicative of the received spectral information. The central processing unit is adapted to compare the electrical signal to an algorithm built upon correlation with the analyte in body fluid, the algorithm adapted to convert the received spectral information into the concentration of the analyte in at least one body fluid.

Description

NON-INVASIVE SYSTEM FOR THE
DETERMINATION OF ANALYTES IN BODY FLUIDS
FIELD OF THE INVENTION
The present invention relates generally to systems for the determination of analytes in body fluids, and, more particularly, to a system for the non-invasive de-termination of analytes in body fluids.
BACKGROUND OF THE INVENTION
Those who have irregular blood glucose concentration levels are medically required to regularly self-monitor their blood glucose concentration level. An irregular blood glucose level can be brought on by a variety of reasons including illness such as diabetes. The purpose of monitoring the blood glucose concentration level is to determine the blood glucose concentration level and then to take corrective action, based upon whether the level is too high or too low, to bring the level back within a normal range. The failure to take corrective action can have serious implications. When blood glucose levels drop too low - a condition known as hypoglycemia - a per-son can become nervous, shaky, and confused. That per-son's judgment may become impaired and that person may eventually pass out. A person can also become very ill if their blood glucose level becomes too high - a condi-tion known as hyperglycemia. Both conditions, hypoglyce-mia and hyperglycemia, are potentially life-threatening emergencies.
Common methods for monitoring a person's blood glu-cose level are invasive in nature. Typically, in order to check the blood glucose level, a drop of blood is ob-tained from the fingertip using a lancing device. The blood drop is produced on the fingertip and the blood is harvested using the test sensor. The test sensor, which is inserted into a testing unit, is brought into contact with the blood drop. The test sensor draws the blood to the inside of the test unit which then determines the concentration of glucose in the blood.

CHICAGO 171 I 03v 1 47082-00031 One problem associated with this type of analysis is that there is a certain amount of pain associated with the lancing of a finger tip. Diabetics must regularly self-test themselves several times per day. Each test requires a separate lancing, each of which involves an instance of pain for the user. Further, each lancing creates a laceration in the users skin which take time to heal and are susceptible to infection just like any other wound.
Other techniques for analyzing a person's blood glu-cose level are noninvasive in nature. Commonly, such techniques interpret the spectral information associated with light that has been transmitted through or reflected from a person' s skin. An advantage of this type of non-invasive analysis is that there is no associated pain or laceration of the skin. However, thus far, such tech-niques have proven unreliable because many techniques fail to recognize the many issues which impact the analy-sis. For example, many noninvasive reflectance and transmission based systems do not account for the fact the obtained spectral data contain glucose information from the portion of body tissue being analyzed as a whole, and is not limited to blood glucose. Other tech-niques do not account for irregularities in the spectral signal of the analyte due instrumental drift, temperature changes in the tissue under analysis, spectral character-istics of the tissue that change due to pressure changes, etc. that can occur during the analysis or between analy-sis. These irregularities can impact the quality of the calibration model or the algorithms that used to deter-mine the analyte concentrations from the noninvasivly collected spectral data. The spectral data that has these irregularities can not be used by the algorithms to determine the analyte concentrations.
Accordingly, there exists a need for a reliable non-invasive system for the determination of analytes in body fluids.

CHICAGO 171103v 1 47082-00031 SUMMARY OF THE INVENTION
A system for determining the concentration of an analyte in at least one body fluid in body tissue com-prises an infrared light source, a body tissue interface, a detector, and a central processing unit. The body tis-sue interface is adapted to contact body tissue and to deliver light from the infrared light source to the con-tacted body tissue. The detector is adapted to receive spectral information corresponding to infrared light transmitted through the portion of body tissue being ana-lyzed and to convert the received spectral information into an electrical signal indicative of the received spectral information. The central processing unit is adapted to compare the electrical signal to an algorithm built upon correlation with the analyte in body fluid, the algorithm adapted to convert the received spectral information into the concentration of the analyte in at least one body fluid.
The above summary of the present invention is not intended to represent each embodiment, or every aspect, of the present invention. Additional features and bene fits of the present invention will become apparent from the detailed description, figures, and claim set forth below.
BRIEF DESCRIPTION OF THE FIGURES
Other objects and advantages of the invention will become apparent upon reading the following detailed description in conjunction with the drawings in which:
FIG. 1 is a functional block diagram of a transmission-based system for determining analytes in body fluids according to one embodiment of the present invention;
FIG. 2 is a plot of the absorbency of transmitted light versus wavelength of the transmitted light according to one embodiment of the transmission-based system illustrated in FIG. 1;

CHICAGO 171103v 1 47082-00031 FIG. 3 is a plot of predicted glucose concentration versus the measured glucose concentration according to one embodiment of the transmission-based system illustrated in FIG. 1;
FIG. 4 is a flow chart depicting a method for building a glucose calibration algorithm according to one embodiment of the present invention;
FIG. 5a is a functional block diagram of a reflectance-based system for determining analytes in body fluids according to one embodiment of the present invention;
FIG. 5b is a cross-sectional view taken along line 5b of FIG. 5a;
FIG. 6 is a plot of the absorbency of reflection light versus wavelength of the reflected light according to one embodiment of the reflected-based system illustrated in FIG. 5a; and FIG. 7 is a plot of predicted glucose concentration versus the measured glucose concentration according to one embodiment of the reflection-based system illustrated in FIG. 5a.
DETAILED DESCRIPTION OF THE ILLUSTRATED EMBODIMENTS , Referring to the drawings and initially to FIG. l, a transmission-based non-invasive system 10 ("the system 10" ) for the determination of analytes in body fluids is functionally illustrated. While the present invention will be discussed in connection with determining a pa-tient's glucose level, the present invention is applica-ble in the analysis of any analyte in body fluid that ex-hibits spectral characteristics. Briefly, the system 10 inputs near infrared light to a piece of skin, such as the "web" of skin between a patient's index finger and thumb, and records the light transmitted through that piece of skin in order to determine the patient's glucose level. Conventionally, a patient's glucose level is re-ferred to as a patient's blood-glucose level. However, to refer to a blood glucose level implies ignoring the CHICAGO 171103v l 47082-00031 amount of glucose contained in a patient's extra-cellular material and inter-cellular material. Accordingly, the inventors of the present invention prefer to refer to a patient's glucose level.
5 Human skin is made of approximately fifty to sixty percent intercellular material with the balance compris-ing extracellular material. The extracellular material comprises approximately one-third plasma (blood) and about two-thirds interstitial fluid ("ISF"). Therefore, when examining the spectral characteristics of glucose from light that is transmitted though a patient's skin, it is important to consider glucose in that portion of skin as a whole, rather than solely the glucose in a pa-tient's blood. The largest portion of the transmitted light is made up of light transmitted though ISF, and not blood. Conversely, in an invasive setting where a 10 ~.1 drop of blood is obtained on a patient's finger tip, for example, the determined glucose concentration primarily represents the concentration of glucose in that patient's blood.
The system 10 is used to obtain transmitted spectral information from a patient. For example, the system 10 is used in a test wherein the glucose concentration of the test subject is modulated to a plurality of different concentration levels. One such test is a glucose clamp-ing test where the glucose level of the test subject is raised and lowered to various levels over the duration of the test. According to one embodiment, the glucose clamping test is designed to bring the test subject's glucose level to six plateau regions that range in con-centration from 50 to 300 mg/dl. Each plateau is sepa-rated by about 50 mg/dl so that each region can be clearly differentiated. ISF and plasma samples are col-lected throughout the duration of the clamping test. The samples are collected every five minutes and are analyzed for glucose content. This measurement is used to adjust the infusion of glucose or insulin to maintain the glu-cose concentration of the plasma for about twenty-five CHICAGO 171103v 1 47082-00031 minutes at a particular targeted plateau region. Very generally, the spectral data obtained over the course of the test are compared to the actual glucose levels (de-termined using invasive techniques) obtained during the test. From this data, a calibration algorithm is built to predict the actual glucose level of the patient based on the spectral characteristics of light transmitted through that patient's skin. This calibration algorithm can then be incorporated into a handheld version of the system 10 illustrated in FIG. 1.
Such a handheld instrument would enable a user to noninvasively monitor the user's glucose concentration level. The user would contact the user's skin with the instrument to obtain spectral information from the user's skin. The instrument would then provide the user with a reading of the user's glucose concentration level a short time later.
Referring back to FIG. 1, an acoustic-optic tunable filter ("AOTF") spectrometer is shown generally by dashed line 12. The AOTF spectrometer 12 outputs a monochro matic, modulated beam of light 14 into a fiber optic ca-ble 16 via a lens 18. The AOTF spectrometer 12 includes a light source 20. According to one embodiment, the light source 20 is a Tungston-Halogen light source, which is a low-cost, stable light source that outputs a good amount of light (e. g., 275 watts). Alternative light sources include light emitting diodes ("LED"), doped fi-bers including uranium doped fibers, and laser diodes.
The light source produces a beam of light 22 in the near-infrared region (i.e., having a wavelength ranging 750-2500 nanometers).
Generally, the AOTF spectrometer 12 functions as an electronically tunable spectral band-pass filter to out-put the monochromatic beam of light 14 having wavelengths within a desired range. The AOTF 12 is a solid state electro-optical device that consists of a crystal 19 in which acoustic (vibrational) waves, at radio frequencies ("RF") are used to separate a single wavelength of light CHICAGO 171103v 1 47082-00031 from a broadband light source. The wavelength selection is a function of the frequency of the RF applied to the crystal 19. The crystal 19 used in AOTF devices can be made from a number of compounds. According to one em-bodiment of the present invention, the crystal of Tellu-rium Dioxide (Te02). Te02 crystals providing good results for use with light in the 1200 to 3000 nm spectral re-gion. According to one embodiment, the crystal 19 is used in a non-collinear configuration, wherein the acous-tic and optical waves (paths) through the crystal 19 are at very different angles from each other. A transducer (not shown) is bonded to one side of the crystal. This transducer emits vibrations (acoustic waves) when RF is applied to the transducer. As the acoustic waves from the transducer to the crystal 19, the crystal 19 alter-nately compresses and relaxes resulting in a refractive index variation that acts like a transmission diffraction grating. Unlike a classical grating, however, the crys-tal only diffracts one specific wavelength of light so it acts like a filter more than a diffraction grating. The wavelength of the light that is diffracted is determined by a phase matching condition based on the birefringence of the Te02 crystal and the velocity and frequency of the acoustical wave and as well as parameters specific to the design of the AOTF. The wavelength that is selected is varied by simply changing the frequency of the applied RF. The diffracted light is directed into two first or-der beams that we called the positive and negative beams.
The rest of the undiffracted light is passed through as undiffracted zero (0) order beam. The two positive and negative beams are orthogonally polarized. The positive beam is delivered to the optoid as described below and the negative beam is used as a reference beam to correct for variations in the intensity of the light source or the efficiency of the AOTF as described below.
According to one embodiment, the beam of light 14 output by the AOTF spectrometer has a resolution or band-width of about four to ten nanometers ("nm"). This band-width is swept (back and forth) across a wavelength range CHICAGO 171103v I 47082-00031 of about 1400 to 2500 nanometers. Put another way, the AOTF spectrometer 12 outputs light having a wavelength continuously ranging between 1400 and 2500 nm and has a resolution of 4-10 nm. The timing of the sweep can range from about one second to several seconds. A suitable AOTF spectrometer is available from Crystal Technologies, Inc. of Palo Alto, California as AOTF Model 2536-O1. The AOTF spectrometer includes a RF driver, a mixer, and RF
oscillator (not shown) for modulating the monochromatic beam of light 14 at approximately 20,000 Hz. A voltage control oscillator (not shown) provides the control of the frequency and the modulation as well as the power levels, which range from 0 to 5.0 watts. A suitable voltage control oscillator is available from the Inrad Corporation, Northvale, New Jersey, Model DVCO-075A010.
The power is delivered to an acoustical transducer that creates an acoustical wave that changes the characteris-tic of a birefringence crystal 19 so that full spectrum light is separated to wavelengths associated with a par-ticular frequency and the rest of the light passes through as zero order light.
The crystal 19 of the AOTF spectrometer 12 splits the beam of light 22 into the first beam 14 and a second beam 23. The second beam of light 23 is directed to a reference detector 24 for measuring/recording the light input to the skin. Additionally, the reference detector 24 measures/records the light 23 for instrument drift as-sociated with the light source and AOTF that can occur over time due to the length of operating time and change in temperature of the instrument over that time period.
The light 14 output by the AOTF spectrometer 12 is directed into a lens 18 that reduces the diameter of the beam of light and focuses the beam of light 14 into an end of the fiber optic cable 16. The lens 18 effectively couples the AOTF spectrometer 12 to the fiber optic cable 16. The fiber optic cable 16 is a low OH (i.e., prefera-bly about 0.3 parts per million of in silica) fiber optic cable which has high attenuation over the length of the CHICAGO 171103v 1 47082-00031 cable. The more OH the greater the intrinsic absorbance of the fiber itself especially in the wavelength region above 2100 nm. According to another embodiment, the fi-ber optic cable has a OH of less than about 0.12 ppm.
The quality of light input to the fiber optic cable 16 is substantially maintained when delivered to a patient's skin at an opposite end 33 of the fiber optic cable 16.
The output end 33 of the fiber optic cable 16 connects to a device the inventor has termed an optoid 34. Gener-ally, the optoid 34 consists of the hardware that inter-faces with the patient' s skin. The optoid 34 includes a first plate 46 and a second plate 48, which are slideably clamped onto the tissue being analyzed, such as the web of skin 52 ("the web 52") of a patient's hand between the index finger and thumb. The optoid 34 includes a sap-phire rod 42 that delivers light from the fiber optic ca-ble 16 to the web 52. The sapphire rod 42, having a di-ameter of about three millimeters in one embodiment, in-creases the diameter of the beam of light input to the web 52. Fiber optic cables are typically limited in di-ameter to about two millimeters. The larger diameter of the sapphire rod 42 provides an effective means of cou-pling light that can be up to 3 mm in beam diameter to be delivered to the skin. Delivering a wider beam of light (e.g., the 3 mm of the sapphire rod as opposed to the 2 mm diameter of the fiber optic cable) covers a larger area of skin which limits the impact of small irregulari-ties in skin properties. The sapphire rod 42 is flush with the interior surface of the first plate 46.
The light that is directed into the web 52 via the sapphire rod 42 is transmitted through the web 52 and into a second sapphire rod 54 (also 3 mm in diameter) disposed within the second plate 48. The light passing through the web 52 is generally represented by arrows 56.
The amount of light transmitted through the web 52 is very low. Typically, less than about two percent of the light exiting the first sapphire rod 42 enters into the second sapphire rod 54. The light transmitted through CHICAGO 171103v 1 47082-0003 l the web 52 is directed by the second sapphire rod 54 into a~ detector 58. According to one embodiment of the pres-ent invention, the detector 58 is an extended Indium Gal-lium Arsenate ("InGaAs") detector having a circular ac-s tive surface of three millimeters in diameter and pro-vides a response across the 1300 to 2500 nm spectral re-gion. Such a detector is commercially available from the Hamamatsu Corporation. According to one embodiment of the present invention, the reference detector 24 and the 10 detector 58 are the same type of detector. Examples of other types of detectors that can be used in alternative embodiments of the present invention include Indium Arse-nide ("InAs"), Indium Selenide ("InSe"), Lead Sulfide ("PbS"), Mercury-Cadmium-Telluride ("MCT"), and DTG de-tectors. Other types of detectors can be used depending on the desired region of the spectrum to be analyzed for determining the glucose concentration level. As is dis-cussed in greater detail below in connection with FIG. 2, glucose exhibits unique spectral characteristics in the about 1450-1850 nm and the about 2200-2500 nm spectral range. The detector 58 generates an electrical signal indicative of the detected transmitted light, which is processed as is described in detail below.
In addition to providing a mechanism for transmit ting light through the web 52, the optoid 34 performs other mechanical functions. First, the moveable first and second plates 46 (also referred to as "jaws") provide pressure to compress the web 52 in order to maintain a consistent optical path through the web 52. Compressing the web 52 brings a greater consistency to the testing process. According to one embodiment, the plates 46,48 compress the tissue approximately six percent. Compress-ing the tissue also creates a flush interface between the web of skin and the plates 46,48 by eliminating air gaps between the web and plates 46,48 so that the light trans-mitted from the first sapphire rod 42 directly enters the web 52. The optoid 34 includes a load cell 56 to measure the contact pressure on the web of skin 52. During the analysis, pressure measurements and temperature measure-CHICAGO 171 103v 1 47082-00031 ments are obtained so that irregularities associated with changes in pressure or temperature can be accounted for as discussed in greater detail below.
Second, each of the plates 46,48 includes thermal s electric heaters (not shown) that heat the web of skin 52 to a uniform temperature. According to one embodiment of the present invention, the thermal-electric heaters heat the web to about 100 °F ~ 0.1 °F. The thermal-electric heaters, which are incorporated into each of the plates, are able to provide very accurate temperature control.
Typically, the temperature differential between the sur-face of skin and the interior ranges between 5-7 °F.
Heating the skin to a substantially uniform level sig-nificantly reduces scattering of the light transmitted through the skin due to temperature gradients resulting in a more consistent analysis. Additionally, heating the skin to about 100 °F expands the capillaries and increases the amount of blood in the capillaries by approximately 300%, thus bringing more glucose into the area of analy sis.
As discussed above, the AOTF 16 modulates the beam of light 14, which causes the beam of light transmitted through the skin via the optoid 34 to be modulated. The modulation aids in resolving some of the issues associ-ated with instrument drift that can effect the quality of the spectral information. The modulated, transmitted light is received by the detector 58 and the modulated transmitted light strikes the active material of the de-tector 58 and is converted by the detector into an elec-trical current indicative of the light received. Accord-ing to one embodiment, the electrical signal generated by the detector 58 is amplified by an amplifier (not shown) and sent to a lock-in amplifier 70, which demodulates the signal. A suitable lock-in amplifier 70 is available from Stanford Research Instruments, Model SR 810 DSP, ac-cording to one embodiment of the present invention. Al-ternatively still, the lock-in amplifier is integrated CHICAGO 171103v I 47082-00031 into an integrated circuit board comprising the described electrical hardware of the present invention.
An analog-to-digital converter 72 then digitizes the demodulated signal. According to one embodiment of the present invention, the analog-to-digital converter is a sixteen-bit converter available from National Instruments Corporation of Austin, Texas. Alternatively, digitiza-tion is incorporated into an integrated circuit board comprising the described electrical hardware of the pres-ent invention. In other alternative embodiments, the digitization is at an 18 bit or higher bit rate.
The spectral data are optionally passed through a high frequency filter 74 to remove high frequency noise and then a low frequency filter 78 to remove slow drift-ing that occurs due to gradual changes in the patient's skin over the course of the analysis, or drift observed in the instrument or the optical fibers. Filtering the signal in this manner improves the overall signal-to-noise ratio.
The signal is then passed on to a central processing unit ("CPU") 78. The CPU 78 averages the received signal every minute resulting in approximately 500 data points over an approximately 500 minute test. The data points are then stored in a memory of the CPU 78. The data are saved with a tracking of the wavelength of the light in-put to the optoid 14 and the corresponding spectral sig-nal produced by the detector 58. The spectral signal is also stored along with the time associated skin tempera-ture, room temperature, pressure applied to the skin dur-ing the measurement, and blood pressure measurements.
This information is useful in determining whether any ir-regularities in the spectral signal are the result of changes in these type of factors and not the result of changes in the glucose concentration. The data are then processed to improve the signal-to-noise quality of the data and to remove artifact effects that can corrupt the quality of the spectral data. According to alternative embodiments of the present invention, the processing to improve the signal-to-noise ratio can be accomplished in CHICAGO 171 103v 1 47082-00031 a variety of manners. For example, in one a7_ternative embodiment, the signal-to-noise quality of the signal is improved by using Wavelet transforms to remove high fre-quency noise and low frequency baseline drift type of noise (i.e., irrelevant spectral variations that are de-termined by the information entropy corresponding to glu-cose levels). According to another alternative embodi-ment, the signal-to-noise quality is improved using such classical methods such as Savitsky-Golay multipoint smoothing. In other embodiments, first derivative analy-sis can be used to deal with baseline issues such as baseline drift type of noise.
Additionally, the noise in the signal is improved by removing spectral information that is not related to the relevant glucose information according to alternative em bodiments of the present invention. This is accomplished by the application of a Genetic Algorithm for selecting wavelength regions that are the most related to the glu-cose changes and removing others that are not. This pro-cess results in the development of robust calibration al-gorithms that significantly reduce overfitting issues.
In still another alternative embodiments, Orthogonal Sig-nal Correction ("OSC") is employed to aid in the removal of non-glucose spectral information from the signal.
This approach has proven beneficial in the removal of temperature and time drift related change imprints on the glucose-related data. Removing the data related to pres-sure and temperature changes over the course of the analysis results in a better calibration algorithm that results in better glucose predictions based on spectral data. Using a combination of approaches results in a more improved signal than using these different ap-proaches individually. For example, the inventors have found that a combination of Wavelet processing and OSC
has produced excellent results. Additionally, the inven-torn have found that the use of Genetic Algorithms in conjunction with OSC has produced excellent results.

CHICAGO 171103v I 47082-00031 Similarly, the reference detector 14 detects the beam of light 23, which is indicative of the light 14 provided to the optoid, and produces a "reference sig nal." The reference signal is processed in a manner similar to the signal produced by the detector 58.
Referring now to FIG. 2, a plot of the percentage of light transmitted through the web versus wavelength (nm) is shown. The peaks in the plot between from about 1450-1850 nm and about 2200-2500 nm show a high absorbency of light 56 transmitted though the tissue. The high absorb ency within these spectral ranges is due, in part, to ab sorption by the water contained in the skin. The glucose in the skin is present, in large part, where the water in the skin is located. Glucose exhibits unique spectral characteristics within these two wavelength ranges.
As mentioned above, during the glucose clamping test, in addition to the transmitted spectral data, sam-ples of blood and ISF are obtained from the test subject (e. g., the patient subjected to the test) to determine the subject's actual blood glucose level. According to one example of the glucose-clamping test, the test is conducted over an approximately 500 minute duration. The blood and ISF samples are obtained about every 5 minutes, totaling about 100 samples. 'These values are then inter-polated over the 500 minute test duration, resulting in about 500 glucose concentration values.
The digital spectral signal of the transmitted light is averaged every minute and stored resulting in about 500 data points over the course of the test duration.
This data is then analyzed and processed (described in greater detail below) to build a calibration algorithm for predicting the actual glucose concentration level from an examination of the spectral characteristics of the transmitted light.
Referring now to FIG. 3, a plot of the predicted glucose value (from spectral characteristics of transmit-ted light) versus the measured glucose value is shown.
As can be seen in the plot of FIG. 3, there is excellent CHICAGO 171103v I 47082-00031 correlation between the predicted glucose concentration and the measured glucose concentration.
In order to obtain the predicted values plotted in FIG. 3, it is necessary to build a calibration algorithm 5 that predicts the glucose concentration from the trans mitted spectral signal (i.e., the signal produced by the detector 58). After the spectral signal is filtered by the high and low frequency filters 74,78, the signal is normalized to correct for changes in the spectral signal 10 which are the results of spectral scattering of the light when transmitted through the web 52 and due to the pres-sure effects of the optoid 34 which is clamped to the web of skin 52. Failure to correct for these changes may ob-scure the spectral information associated with the glu-15 cose. As stated above, less than approximately two per-cent of the light input to the web of skin 52 is trans-mitted to the detector 58. Accordingly, it is important to account for these types of changes and irregularities than can lead to errors. The raw signal from the AOTF
spectrometer described above is first normalized to con-stant energy, then mean centered to remove constant areas of the spectrum, creating a normalized, preprocessed se-ries of spectra that are then checked for outliers by standard methods well known in the art. Further preproc-essing by OSC reduction and wavelets analysis filtering are done to enhance the glucose signal and to suppress the water and other background signals. The resulting set of spectra is then used to build a calibration model by partial least squares (PLS) regression using Venetian blinds cross-validation on a portion of the data de-scribed above or on all of the data. Alternative embodi-ments to the data preparation described above involve other common methods for reduction or removal of back-ground signal, including, but not limited to, first-derivative smoothing, second-derivative smoothing, wave-length selection by means of genetic algorithms, wavelet processing, and principal components analysis. Alterna-tive embodiments for the generation of calibration models CHICAGO 171103v 1 47082-00031 can be realized by many different forms of regression, including principal components regression, ridge regres-sion or ordinary (inverse) least squares regression.
The calibration algorithm to predict the glucose concentration is then built .from the normalized signal.
An orthogonal signal correction process is combined with the time associated temperature and pressure information to identify the parts of the spectrum that are associated with these factors and not strictly related to the changes in the glucose concentration. This process is used in combination with the correlated data (i.e., the invasively determined glucose concentrations of the plasma and the ISF fluids) to filter out of the spectral data information that is associated with changes in the other measurements and not with changes in the glucose.
This results in a calibration algorithm that is much more clearly associated with the changes in the glucose con-centration, and less with artifacts that happen to corre-late to the glucose concentration. Other data improve-ment processes include the use of more generic che-mometric applications such as Genetic Algorithms and Wavelet analysis to further refine the spectral informa-tion to the most efficient information. The Genetic al-gorithm and Wavelet analysis are able to select wave-lengths in the spectrum that are specifically related to glucose and to permit the calibration algorithm to focus on specific changes in the glucose concentration. The selection is based on the area of the spectrum where the strongest glucose related peaks are located, but also the spectral areas related to the changes in the refractive index of the tissue due to changes in the tissue concen-tration. This wavelength selection process results in retaining the wavelength information that produces the best calibration algorithm .
Referring now to FIG. 4, a flow chart depicting a method of building the glucose calibration algorithm will be described according to one embodiment of the present invention. Initially, as described above, a glucose CHICAGO 171103v 1 47082-00031 clamping experiment is conducted wherein spectral infor-mation is obtained from the body tissue of at least a first and a second test subject. This information is stored in a first data set 82 and a second data set 83.
In one embodiment, the first and second data sets 82, 83 each include spectral information obtain from a plurality of test subjects. Other information such as body tissue temperate, pressure applied to the body tissue, and the invasively determined glucose concentration levels are obtained from each of the test subjects at predetermined intervals during the glucose clamping test.
A combined data set, consisting of spectral data from more than one test subjects (e.g., data from the first and second spectral data sets 82, 84), is prepared and used to generate a model useful for prediction of glucose levels for all of the subjects contributing data.
The raw signals, stored in the first and second data sets 82, 84, from the AOTF spectrometer described above are first normalized at step 84 to constant energy for data from each of the test subjects. Portions of the data for each subject are then combined to form a single, combined spectral set at step 85, which is then mean centered at step 86 to remove constant areas of the spectrum, creat-ing a normalized, preprocessed series of spectra that are then checked for outliers by standard methods known in the art. Further preprocessing by OSC reduction and wavelets analysis filtering are done to enhance the glu-cose signal and to suppress the water and other back-ground signals. The resulting set of spectra is then used to build a calibration model by partial least squares (PLS) regression as step 87 using Venetian blinds cross-validation on a portion of the data described above or on all of the data. Alternative embodiments to the data preparation described above involve other common methods for reduction or removal of background signal, including, but not limited to, first-derivative smoothing, second-derivative smoothing, wavelength selection by means of genetic algorithms, wavelet processing and prin-CHICAGO 171 103v1 47082-00031 cipal components analysis. Alternative embodiments for the generation of calibration models can be realized by many different forms of regression, including principal components regression, ridge regression or ordinary (in s verse) least squares regression.
The PLS model, which was created at step 87, is ap-plied to the orthogonal signal corrected, normalized first data set at step 89, which results in the glucose calibration algorithm at step 90. The glucose calibra-tion algorithm 90 is used to predict glucose concentra-tion based upon spectral information obtained from a test subject. Put another way, the glucose calibration algo-rithm is able to determine the glucose concentration of a test subject based upon the spectral information (e. g., transmitted or reflected spectral information) obtained from a test subject. The glucose calibration algorithm 90 is then applied to the orthogonal signal corrected, normalized second data set at step 91 for predicting the glucose contraction values of the test subjects) of the second spectral data set 83 at step 92. The glucose con-centration values predicted at step 92 are then compared to the invasively determined glucose concentration ob-tained during the glucose clamping test to check the ac-curacy of the glucose calibration algorithm at step 93.
In an alternative embodiment of the present inven-tion, building the glucose calibration algorithm also in-cludes applying a Wavelets analysis to each of the data sets after OSC step 88, which filters the data. Addi-tionally, in other alternative embodiments of the present invention, the spectral data sets 82, 83 include spectral data modeled for glucose concentration levels which are outside the range of glucose concentration levels achieved during the glucose clamping test. In one em-bodiment, the AOTF spectrometer 16 can be used to create spectral data outside the ranges achieve during the glu-cose clamping test.
Referring now to FIGS. 5a and 5b, a reflectance-based non-invasive system 90 ("the system 90") for the CHICAGO 171103v 1 47082-0003 l CHICAGO 171 103v1 47082-00031 determination of analytes in body fluids is functionally illustrated. Briefly, the system 90 inputs near infrared light into a portion of a patient's skin, such as a fore-arm, and records the amount of light reflected from the skin in order to determine the patient's glucose level.
A monochromatic beam of light is input to a bundle 100 of fiber optic cables 101. While the bundle 100 of fiber optic cables depicted in FIG. 4b shows two concen-tric circles or rows of fiber optic cables 101, any rea-sonable number of rows of fiber optic cable can be used.
The monochromatic beam of light is generated in a manner similar to that described in connection with FIG. 1. An AOTF spectrometer (not shown) outputs a beam of light 44 having a resolution of four to ten nanometers ("nm"), which is swept (back and forth) across a wavelength range of about 2200-4500 nanometers to the fiber optic cable bundle 100. The fiber optic cable bundle 100 delivers light 94 to an optoid 104. The optoid 104 consists of the hardware that interfaces with a patient's skin. The . optoid 104 includes a plate 106 having a window 108.
Light 102 is directed through the window 108 onto the pa-tient's skin 110. According to one embodiment of the present invention, the window 108 is a sapphire window.
In use, the optoid 104 is brought into contact with a patient's skin 110 such as the patient's forearm, such that skin 110 rests on the plate 106 and window 108.
Light 102 is directed through the window 108 into the skin 110. The light penetrates the skin 110 to a depth of about 300 microns and is then reflected from inside the skin 110. The reflected light is represent by arrows 112. The reflected light 112 is directed to a detector 114 via a sapphire rod 116 disposed within the fiber op tic bundle 100. The reflected light 112 is detected by the detector 114 in a manner similar to the transmitted light 56 discussed in connection with FIG. 1.
According to an alternative embodiment of the re-flectance-based, non-invasive system 90, only a portion of the fiber optic cables 101 are used to deliver light to the optoid 104 which varies the path length of the de-CHICAGO 171103v1 47082-00031 livered light. For example, only an inner ring of fiber optic cables 101 be utilized according to one embodiment and only the outer ring of finger optic cables 101 are utilized according to another embodiment. Varying the 5 path length of the delivered allows the sampling of re-flected light from different depths in the tissue. Ac-cording to some embodiments, the various path lengths are used to correct for individual tissue characteristics such as scattering.
10 The optoid 104 of the reflectance-based non-invasive system 90 provides temperature control to the area of skin from which the reflectance signal is being taken.
According to one embodiment of the present invention, the plates 106 of the optoid include thermoelectric heaters 15 for heating the skin to approximately 100° ~ 0.1 °F.
Again, heating the skin to uniform temperature reduces scattering of light, which is a function of temperature.
Additionally, as discussed above, heating the skin causes the capillaries to expand thus increasing the volume of 20 blood in the capillaries approximately three hundred per-cent.
According to one embodiment of the present inven-tion, an index matching material 112 is disposed between the skin 110 and the sapphire window 108, for maintaining a constant and matched index for the light 102 directed into the skin 110 and the light reflected from the skin 112. The index matching gel reduces large index of re-fraction changes that would occur normally between skin and a gap of air. These large changes result in Fresnel losses that are especially significant in a reflectance based analysis, which creates significant changes in the spectral signal. According t.o one embodiment of the pre-sent invention, the indexing matching material 112 is a chloro-fluoro-carbon gel. This type of indexing material has several favorable properties. First, the chloro-fluoro-carbon gel minimally impacts the spectral signal directed through the gel. Second, this indexing matching material has a high fluid temperature point so that it CHICAGO 171103v 1 47082-00031 remains in a gel-like state during the analysis and under test conditions. Third, this gel exhibits hydrophobic properties so that it seals the sweat glands so that sweat does not fog-up (i.e., form a liquid vapor on) the sapphire window 108. And fourth, this type of index matching material will not be absorbed into the stratum corneum during the analysis.
The output of the detector 114 is filtered and proc essed in a manner similar to that described in conjunc tion with the above-described transmission-based system 10.
Referring now to FIG. 5, a plot of the absorption of light input to the skin versus wavelength is shown. As can be seen in FIG. 5, high absorption is observed in the 1350-1600 nm and the 1850-2100 spectral range.
The calibration algorithm for the reflectance-based system is built by applying similar data processing tech-niques as discussed in connection with the transmission-based system. Referring now to FIG. 6, a plot of the predicted glucose concentration using the calibration al gorithm versus the measured glucose concentration (ob tained invasively) is shown. As in the case of the transmission-based system 10, the reflectance-based sys tem 90 provides an accurate prediction of the test sub ject's glucose concentration.
While the present invention has been described with reference to one or more particular embodiments, those skilled in the art will recognize that many changes may be made thereto without departing from the spirit and scope of the present invention. Each of these embodi-ments and obvious variations thereof is contemplated as falling within the spirit and scope of the claimed inven-tion, which is set forth in the following claims.

CHICAGO 171103v 1 47082-00031

Claims (112)

WHAT IS CLAIMED IS:
1. A system for determining the concentration of an analyte in at least one body fluid in body tissue, the system comprising:
an infrared light source;
a body tissue interface adapted to contact body tis-sue and to deliver light from the infrared light source to the contacted body tissue;
a detector adapted to receive spectral information corresponding to infrared light transmitted through the portion of body tissue being analyzed and to convert the received spectral information into an electrical signal indicative of the received spectral information; and a central processing unit adapted to compare the electrical signal to an algorithm built upon correlation with the analyte in body fluid, the algorithm adapted to convert the received spectral information into the con-centration of the analyte in at least one body fluid.
2. The system of claim 1 wherein narrow wavelength ranges of infrared light are selectively delivered to the body tissue interface.
3. The system of claim 1 wherein the light deliv-ered to the body tissue interface is a monochromatic light.
4. The system of claim 1 further comprising an acoustic optical tunable filter for receiving the infra-red light from the infrared light source and outputting a monochromatic beam of light to the body tissue interface.
5. The system of claim 4 further comprising a ref-erence detector adapted to receive a portion of the mono-chromatic light output by the acoustic optical tunable filter and to convert the received light into a reference electrical signal.
6. The system of claim 5 wherein the acoustic , op-tical tunable filter is adapted to modulate the monochro-matic beam of light, and further comprising at least one lock-in amplifier electrically for demodulating the ref-erence electrical signal and for demodulating the elec-trical signal indicative of the received spectral infor-mation.
7. The system of claim 1 further comprising at least one fiber optic cable adapted to deliver the infra-red light to the body tissue interface.
8. The system of claim 7 wherein the at least one fiber optic cable is a low OH fiber optic cable.
9. The system of claim 8 wherein the at least one fiber optic cables has an OH of less than 0.12 ppm.
10. The system of claim 1 wherein the body tissue interface comprises a clamping device having two plates for contacting the body tissue.
11. The system of claim 10 wherein the body tissue interface includes a first sapphire rod for receiving light from the infrared light source and directing the infrared light onto the body tissue and a second sapphire rod for receiving infrared light transmitted through the body tissue and delivering the transmitted light to the detector.
12. The system of claim 10 wherein the clamping de-vice is adapted to compress the contacted body tissue.
13. The system of claim 10 further including a load cell for measuring an amount of pressure applied to the body tissue by the clamping device.
14. The system of claim 13 wherein the tissue is compressed approximately five to ten percent by the clamping device.
15. The system of claim 10 wherein at least one of the two plates includes a temperature control element for controlling the temperature of the body tissue contacted by the clamping device.
16. The system of claim 15 wherein the temperature control element is a thermal electric device.
17. The system of claim 15 wherein the temperature control element is adapted to control the temperature of the contacted body tissue to a temperature ranging be-tween about 50 °F and 105 °F.
18. The system of claim 17 wherein the temperature control element is adapted to control the temperature of the contacted body tissue to a temperature ranging be-tween about 99 °F and 101 °F.
19. The system of claim 1 wherein the detector is an extended Indium Gallium Arsenate detector.
20. The system of claim 1 wherein the light output by the infrared light source has a wavelength ranging be-tween approximately 750 nanometers and approximately 11,000 nanometers.
21. The system of claim 20 wherein the wavelength ranges between approximately 1400 nanometers and 11,000 nanometers.
22. The system of claim 21 wherein the wavelength ranges between approximately 1400 nanometers and 2500 na-nometers.
23. The system of claim 1 wherein the at least one body fluid is plasma.
24. The system of claim 1 wherein the at least one body fluid is interstitial fluid.
25. The system of claim 1 wherein the at least one body fluid includes intercellular fluid.
26. The system of claim 1 wherein the at least one body fluid is intracellular fluid.
27. The system of claim 1 wherein the analyte is glucose.
28. The system of claim 1 wherein the detector com-prises a diode array and further includes a grating for filtering the infrared light transmitted through the body tissue.
29. The system of claim 1 further comprising an acoustic optical tunable filter for receiving the trans-mitted infrared light and outputting predetermined wave-length bands of the transmitted light to detector.
30. A method for determining the concentration of an analyte in at least one body fluid in body tissue, the method comprising:
contacting body tissue to be analyzed;
compressing the contacted body tissue;
controlling the temperature of the body tissue such that the body tissue is maintained at substantially uni-form temperature;
directing infrared light into the body tissue;
detecting infrared light transmitted through the body tissue;
analyzing the detected transmitted light using an algorithm built upon correlation with the analyte in the body fluid, the algorithm being adapted to convert the detected transmitted light into the concentration of the analyte in at least one body fluid; and determining the concentration of the analyte in at least one body fluid.
31. The method of claim 30 further comprising meas-uring an amount of pressure applied to the body tissue being analyzed.
32. The method of claim 30 wherein controlling the temperature further comprises controlling the temperature with thermal electrical devices.
33. The system of claim 30 wherein the controlling the temperature further comprises controlling the of the body tissue to a temperature ranging between about 50 °F
and about 105 °F.
34. The system of claim 33 wherein the controlling the temperature further comprises controlling the of the body tissue to a temperature ranging between about 99 °F
and about 101 °F.
35. The method of claim 30 wherein detecting fur-ther comprises detecting the transmitted light with an extended Indium Gallium Arsenate detector.
36. The method of claim 30 wherein directing infra-red light further comprises selectively directing narrow bandwidths of infrared light.
37. The method of claim 30 wherein directing infra-red light further comprises directing monochromatic light onto the body tissue.
38. The method of claim 30 wherein directing fur-ther comprises:
directing the infrared light to an acoustic optical tunable filter; and outputting a monochromatic beam of light from the acoustic optical tunable filter onto the contacted body tissue.
39. The method of claim 38 further comprising de-tecting a portion of monochromatic light output by the acoustic optical tunable filter with a reference detec-tor.
40. The method of claim 39 further comprising:
modulating the monochromatic beam of light output by the acoustic optical tunable filter, demodulating the monochromatic light received by the reference detector; and demodulating the detected transmitted light.
41. The method of claim 30 wherein directing mono-chromatic light further comprises directing a beam of monochromatic light having a wavelength ranging between approximately 750 nanometers and approximately 11,000 na-nometers.
42. The system of claim 41 wherein the wavelength ranges between approximately 1400 nanometers and 11,000 nanometers.
43. The system of claim 41 wherein the wavelength ranges between approximately 1400 nanometers and 2500 na-nometers.
44. The system of claim 34 wherein the at least one body fluid is plasma.
45. The system of claim 30 wherein the at least one body fluid is interstitial fluid.
46. The system of claim 30 wherein the at least one body fluid is intercellular fluid.
47. The system of claim 30 wherein the at least one body fluid is intracellular fluid.
48. The system of claim 30 wherein the analyte is glucose.
49. A system for determining the concentration of an analyte in at least one body fluid in body tissue, the system comprising:
an infrared light source;
a body tissue interface adapted to contact body tis-sue and to deliver light from the infrared light source to contacted body tissue;
an index matching medium disposed between the body tissue interface and the received body tissue, wherein the infrared light delivered to the body tissue and re-flected by the body tissue passes through the index matching medium;
a detector adapted to receive light reflected from the body fluid and to convert the received reflected light into an electrical signal indicative of the re-ceived reflected light; and a central processing unit adapted to compare the electrical signal to an algorithm built upon correlation with the analyte in body fluids, the algorithm converting the received spectral information into the concentration of the analyte in at least one body fluid.
50. The system of claim 49 wherein the body tissue interface comprises a an plate having a translucent win-dow allowing light to pass through, the plate and window having an upper surface and a lower surface, the upper surface being adapted to contact the body tissue.
51. The system of claim 50 wherein the plate in-cludes a temperature control device for controlling the temperature of the contacted body tissue.
52. The system of claim 50 wherein the temperature control element is adapted control the temperature of the contacted body tissue to a temperature ranging between about 50 °F and 105 °F .
53. The system of claim 52 wherein the, temperature control element is adapted to control the temperature of the contacted body tissue to a temperature ranging be-tween about 99 °F and 101 °F.
54. The system of claim 51 wherein the temperature control device is a thermal electric device.
55. The system of claim 49 wherein the detector is an extended Indium Gallium Arsenate detector.
56. The system of claim 30 wherein narrow band-widths of infrared light are selectively delivered to the to contacted body tissue.
57. The method of claim 30 wherein the light deliv-ered to the contracted body tissue is monochromatic light.
58. The method of claim 30 wherein directing fur-ther comprises:
directing the infrared light to an acoustic optical tunable filter; and outputting a monochromatic beam of light from the acoustic optical tunable filter onto the contacted body tissue.
59. The system of claim 32 further comprising an acoustic optical tunable filter for receiving the infra-red light from the infrared light source and outputting a monochromatic beam of light to the body tissue interface.
60. The system of claim 59 further comprising a reference detector for receiving a portion of the mono-chromatic light output by the acoustic optical tunable filter and for and converting the received light into a reference electrical signal.
61. The system of claim 59 wherein the acoustic op-tical tunable filter is adapted to modulate the monochro-matic beam of light, and further comprising al least one lock-in amplifier for demodulating the reference electri-cal signal and for demodulating the electrical signal in-dicative of the received reflected light.
62. The system of claim 59 further comprising a plurality of fiber optic cables adapted to deliver light received from the acoustic optical tunable filter to the body tissue interface.
63. The system of claims 62 wherein a portion of the plurality of fiber optic cables are selectively used for delivering light such that a path length of the de-livered light varies according to which portion of the plurality of fiber of the are utilized, a portion of the plurality of fiber optic cables including at least one fiber optic cable.
64. The system of claim 62 further comprising a light collection device for delivering the reflected light to the detector.
65. The system of claim 64 wherein the light col-lection device is selected from the group consisting of a sapphire rod, a sapphire window, a spherical optical col-lection device, and an elliptical collection device.
66. The system of claim 64 wherein the light col-lection device is a sapphire rod.
67. The system of claims 66 wherein the sapphire rod is disposed within the plurality of fiber optic ca-bles.
68. The system of claim 64 wherein each of the plu-rality of fiber optic cables are low OH fiber optic ca-bles.
69. The system of claim 64 wherein each of the plu-rality of fiber optic cables are hollow fiber optic ca-bles.
70. The system of claim 64 wherein each of the plu-rality of fiber optic cables has an OH of less than 0.12 ppm.
71. The system of claim 49 wherein the infrared light has a wavelength ranging between approximately 750 nanometers and approximately 11,000 nanometers.
72. The system of claim 71 wherein the infrared light has a wavelength ranging between approximately 1400 nanometers and approximately 11,000 nanometers.
73. The system of claim 72 wherein the infrared light has a wavelength ranging between approximately 1400 nanometers and approximately 2500 nanometers.
74. The system of claim 49 wherein the index match-ing medium is a chloro-fluoro-carbon gel.
75. The system of claim 49 wherein the detector comprises a diode array and further includes a grating for filtering the infrared light reflected from the body fluid.
76. The system of claim 49 further comprising an acoustic optical tunable filter for receiving the re-flected infrared light and outputting predetermined wave-length bands of the transmitted light to detector.
77. A method for determining the concentration of an analyte in at least one body fluid in body tissue, the method comprising:
disposing an index matching medium an a surface of a body tissue interface;
contacting body tissue with the body tissue inter-face;
controlling the temperature of a contacted the body tissue to a substantially uniform temperature;
directing a beam of infrared light onto the body tissue;
detecting infrared light reflected from the body tissue;
comparing the detected reflected light to an algo-rithm built upon correlation with the analyte in body fluid, the algorithm adapted to convert the detected re-flected light into the concentration of the analyte in at least one body fluid; and determining the concentration of the analyte in at least one body fluid.
78. The method of claim 77 wherein controlling the temperature further comprises controlling with thermal electrical devices.
79. The system of claim 77 wherein the controlling the temperature further comprises controlling the of the body tissue to a temperature ranging between about 50 °F
and about 105 °F.
80. The system of claim 79 wherein the controlling the temperature further comprises controlling the of the body tissue to a temperature ranging between about 99 °F
and about 101 °F .
81. The method of claim 77 wherein detecting fur-ther comprises detecting the light transmitted through the portion of body tissue being analyzed with an ex-tended Indium Gallium Arsenate detector.
82. The method of claim 77 wherein directing infra-red light further comprises selectively directing narrow bandwidths of infrared light.
83. The method of claim 77 wherein directing infra-red light further comprises directing monochromatic light onto the body tissue.
84. The method of claim 77 wherein directing fur-ther comprises:
receiving a beam of infrared light with an acoustic optical tunable filter;
outputting a monochromatic beam of light from the acoustic optical tunable filter; and directing the monochromatic light onto the body tis-sue.
85. The method of claim 84 further comprising de-tecting a portion of the monochromatic light directed onto the body tissue with a reference detector.
86. The method of claim 85 further comprising:
modulating the monochromatic beam of light output from the output by the acoustic optical tunable filter, demodulating the monochromatic light received by the reference detector; and demodulating the infrared light reflected from the body tissue.
87. The system of claim 84 wherein the infrared light has a wavelength ranging between approximately 1400 nanometers and approximately 11,000 nanometers.
88. The system of claim 87 wherein the infrared light has a wavelength ranging between approximately 1400 nanometers and approximately 2500 nanometers.
89. The system of claim 88. wherein the index matching medium is a chloro-fluoro-carbon gel.
90. The method of claim 77 wherein disposing an in-dex matching medium further comprises disposing a chloro-fluoro-carbon gel on the surface of a plate.
91. The method of 77 further comprising delivering the reflected light to a detector with a sapphire rod.
92. The method of 77 wherein directing further com-prises directing the infrared light through a plurality of fiber optic cables.
93. The system of claim 77 wherein the at least one body fluid is plasma.
94. The system of claim 77 wherein the at least one body fluid is interstitial fluid.
95. The system of claim 77 wherein the at least one body fluid is intercellular fluid.
96. The system of claim 77 wherein the at least one body fluid is intracellular fluid.
97. The system of claim 77 wherein the analyte is glucose.
98. A method for building an algorithm for convert-ing spectral information obtained from body tissue into the concentration of glucose in at least one body fluid in the body tissue, the method comprising:
modulating the concentration of glucose in at least one body fluid in the body tissue to a plurality of pre-determined levels within a range of predetermined glucose concentration levels;
directing infrared light onto the body tissue of at least one test subject being analyzed during a glucose clamping test;
collecting spectral information from the body tis-sue;
collecting data other than spectral information from body tissue of the at least one test subject during the modulating of the concentration of glucose in at least one body fluid in the body tissue, modeling spectral information corresponding to glu-cose concentration levels outside the range of glucose concentration levels; and filtering the collected and modeled spectral infor-mation to remove non-analyte spectral information using one or more established chemometric techniques selected from the group consisting of wavelets analysis, orthogo-nal signal correction, partial least squares regression, principal components analysis, and genetic algorithms.
99. The method of claim 98 further comprising re-cording invasively determined glucose concentration lev-els of the body tissue of the at least one test subject in a invasively determined glucose data set.
100. The method of claim 99 further comprising re-cording the collected spectral information and the mod-eled spectral information in a spectral data set.
101. The method of claim 100 further comprising nor-malizing the data of the spectral data set.
102. The method of claim 101 further comprises ap-plying an orthogonal signal correction analysis to the normalized data set to create a corrected spectral data set.
103. The method of claim 102 further comprising fil-tering the corrected spectral data set by applying a wavelet analysis to form a filtered spectral data set.
104. The method of claim 103 further comprising ap-plying a partial least squares regression analysis to the filtered spectral data set and the invasively determined glucose data set to build a glucose calibration algo-rithm.
105. The method of claim 98 wherein modulating fur-ther comprises conducting a glucose clamping experiment.
106. The method of claim 98 wherein the data are se-lected from the group consisting of invasively determined glucose concentration levels of the body tissue, tempera-ture of the body tissue, pressure applied to the body tissue, frequency of the infrared light directed onto the body tissue, and time of data collection.
107. A method for building an algorithm for convert-ing spectral information obtained from body tissue into the concentration of glucose in at least one body fluid in the body tissue, wherein the glucose concentration level of the at least one body fluid in body tissue of a plurality of test subjects including a first test subject and a second test subject is modulated to a plurality of predetermined glucose concentration levels within a range of glucose concentration levels, the method comprising:
invasively determining the glucose concentration levels of the at least one body fluid of each of the test subjects during the modulating of glucose concentration levels of the at least one body fluid in body tissue;

directing infrared light onto the body tissue the test subjects being analyzed during the glucose clamping test;
collecting spectral information from the body tissue of the test subjects;
normalizing the information collected from the body tissue of the test subjects;
combining a portion of the normalized spectral in-formation collected from the first test subject with a portion of the normalized spectral information collected from the second test subject to create a combined spec-tral data set;
mean centering the combined spectral data set;
creating a partial least squares regression model having at least one orthogonal signal correction compo-nent from the combined spectral data set, the partial least squares regression model being adapted to filter out non-glucose related spectral information form the spectral data set;
applying an orthogonal signal correction analysis to the normalized spectral information collected from the first test subject to form a first corrected data set and to the normalized spectral information collected from the second test subject from a second corrected data set; and applying the partial least squares regression model to first corrected data set and the invasively determined glucose concentration levels collected from the first test subject to form the algorithm for converting spec-tral information obtained from body tissue into the con-centration of glucose in at least one body fluid in the body tissue.
108. The method of claim 107 further comprising ap-plying the algorithm to the second corrected data set for predicting the glucose concentration levels of the at least one body fluid in the body tissue of the second test subject.
109. The method of claim 108 further comprising com-paring the predicted glucose concentration levels of the at least one body fluid in the body tissue of the second test subject to the invasively determined the glucose concentration levels collected from the second test sub-ject during the glucose clamping test.
110. The method of claim 107 further comprising fil-tering the first and the second corrected spectral data set by applying a wavelet analysis prior to applying the partial least squares regression model.
111. The method of claim 107 further comprising col-lecting data other than spectral information during the during the modulating of glucose concentration levels, the data being selected from the group consisting of a target body fluid glucose concentration for each test subject, temperature of the body tissue for each test subject, pressure applied to the body tissue of each test subject, frequency of the infrared light directed onto the body tissue of each test subject, and time of data collection.
112. The method of claim 107 further comprising:
modeling spectral information corresponding to glu-cose concentration levels outside the range of glucose concentration levels; and combining the modeled spectral information with the collected spectral information from the body tissue of the test subjects.
CA002418399A 2002-02-11 2003-02-04 Non-invasive system for the determination of analytes in body fluids Abandoned CA2418399A1 (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US35535802P 2002-02-11 2002-02-11
US60/355,358 2002-02-11

Publications (1)

Publication Number Publication Date
CA2418399A1 true CA2418399A1 (en) 2003-08-11

Family

ID=27613551

Family Applications (1)

Application Number Title Priority Date Filing Date
CA002418399A Abandoned CA2418399A1 (en) 2002-02-11 2003-02-04 Non-invasive system for the determination of analytes in body fluids

Country Status (5)

Country Link
US (4) US7299079B2 (en)
EP (2) EP2400288A1 (en)
JP (1) JP4476552B2 (en)
AU (1) AU2003200359A1 (en)
CA (1) CA2418399A1 (en)

Families Citing this family (127)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6391005B1 (en) 1998-03-30 2002-05-21 Agilent Technologies, Inc. Apparatus and method for penetration with shaft having a sensor for sensing penetration depth
US6949816B2 (en) * 2003-04-21 2005-09-27 Motorola, Inc. Semiconductor component having first surface area for electrically coupling to a semiconductor chip and second surface area for electrically coupling to a substrate, and method of manufacturing same
US6522903B1 (en) 2000-10-19 2003-02-18 Medoptix, Inc. Glucose measurement utilizing non-invasive assessment methods
US8641644B2 (en) 2000-11-21 2014-02-04 Sanofi-Aventis Deutschland Gmbh Blood testing apparatus having a rotatable cartridge with multiple lancing elements and testing means
ATE485766T1 (en) 2001-06-12 2010-11-15 Pelikan Technologies Inc ELECTRICAL ACTUATING ELEMENT FOR A LANCET
US7981056B2 (en) 2002-04-19 2011-07-19 Pelikan Technologies, Inc. Methods and apparatus for lancet actuation
US8337419B2 (en) 2002-04-19 2012-12-25 Sanofi-Aventis Deutschland Gmbh Tissue penetration device
US9795747B2 (en) 2010-06-02 2017-10-24 Sanofi-Aventis Deutschland Gmbh Methods and apparatus for lancet actuation
US9226699B2 (en) 2002-04-19 2016-01-05 Sanofi-Aventis Deutschland Gmbh Body fluid sampling module with a continuous compression tissue interface surface
US7749174B2 (en) 2001-06-12 2010-07-06 Pelikan Technologies, Inc. Method and apparatus for lancet launching device intergrated onto a blood-sampling cartridge
DE60234598D1 (en) 2001-06-12 2010-01-14 Pelikan Technologies Inc SELF-OPTIMIZING LANZET DEVICE WITH ADAPTANT FOR TEMPORAL FLUCTUATIONS OF SKIN PROPERTIES
US9427532B2 (en) 2001-06-12 2016-08-30 Sanofi-Aventis Deutschland Gmbh Tissue penetration device
US7025774B2 (en) 2001-06-12 2006-04-11 Pelikan Technologies, Inc. Tissue penetration device
CA2418399A1 (en) 2002-02-11 2003-08-11 Bayer Healthcare, Llc Non-invasive system for the determination of analytes in body fluids
US7892183B2 (en) 2002-04-19 2011-02-22 Pelikan Technologies, Inc. Method and apparatus for body fluid sampling and analyte sensing
US7331931B2 (en) 2002-04-19 2008-02-19 Pelikan Technologies, Inc. Method and apparatus for penetrating tissue
US7901362B2 (en) 2002-04-19 2011-03-08 Pelikan Technologies, Inc. Method and apparatus for penetrating tissue
US7976476B2 (en) 2002-04-19 2011-07-12 Pelikan Technologies, Inc. Device and method for variable speed lancet
US7892185B2 (en) 2002-04-19 2011-02-22 Pelikan Technologies, Inc. Method and apparatus for body fluid sampling and analyte sensing
US7909778B2 (en) 2002-04-19 2011-03-22 Pelikan Technologies, Inc. Method and apparatus for penetrating tissue
US8360992B2 (en) 2002-04-19 2013-01-29 Sanofi-Aventis Deutschland Gmbh Method and apparatus for penetrating tissue
US7175642B2 (en) 2002-04-19 2007-02-13 Pelikan Technologies, Inc. Methods and apparatus for lancet actuation
US7547287B2 (en) 2002-04-19 2009-06-16 Pelikan Technologies, Inc. Method and apparatus for penetrating tissue
US8221334B2 (en) 2002-04-19 2012-07-17 Sanofi-Aventis Deutschland Gmbh Method and apparatus for penetrating tissue
US7229458B2 (en) 2002-04-19 2007-06-12 Pelikan Technologies, Inc. Method and apparatus for penetrating tissue
US7491178B2 (en) 2002-04-19 2009-02-17 Pelikan Technologies, Inc. Method and apparatus for penetrating tissue
US7297122B2 (en) 2002-04-19 2007-11-20 Pelikan Technologies, Inc. Method and apparatus for penetrating tissue
US9795334B2 (en) 2002-04-19 2017-10-24 Sanofi-Aventis Deutschland Gmbh Method and apparatus for penetrating tissue
US8702624B2 (en) 2006-09-29 2014-04-22 Sanofi-Aventis Deutschland Gmbh Analyte measurement device with a single shot actuator
US9314194B2 (en) 2002-04-19 2016-04-19 Sanofi-Aventis Deutschland Gmbh Tissue penetration device
US8267870B2 (en) 2002-04-19 2012-09-18 Sanofi-Aventis Deutschland Gmbh Method and apparatus for body fluid sampling with hybrid actuation
US8784335B2 (en) 2002-04-19 2014-07-22 Sanofi-Aventis Deutschland Gmbh Body fluid sampling device with a capacitive sensor
US7226461B2 (en) 2002-04-19 2007-06-05 Pelikan Technologies, Inc. Method and apparatus for a multi-use body fluid sampling device with sterility barrier release
US7232451B2 (en) 2002-04-19 2007-06-19 Pelikan Technologies, Inc. Method and apparatus for penetrating tissue
US9248267B2 (en) 2002-04-19 2016-02-02 Sanofi-Aventis Deustchland Gmbh Tissue penetration device
US7674232B2 (en) 2002-04-19 2010-03-09 Pelikan Technologies, Inc. Method and apparatus for penetrating tissue
US8579831B2 (en) 2002-04-19 2013-11-12 Sanofi-Aventis Deutschland Gmbh Method and apparatus for penetrating tissue
CN100406872C (en) * 2002-11-04 2008-07-30 天津市先石光学技术有限公司 Composite spectral measurement method and its spectral detection instrument
US8574895B2 (en) 2002-12-30 2013-11-05 Sanofi-Aventis Deutschland Gmbh Method and apparatus using optical techniques to measure analyte levels
US7153256B2 (en) 2003-03-07 2006-12-26 Neuronetics, Inc. Reducing discomfort caused by electrical stimulation
US8118722B2 (en) 2003-03-07 2012-02-21 Neuronetics, Inc. Reducing discomfort caused by electrical stimulation
KR100464324B1 (en) * 2003-03-17 2005-01-03 삼성전자주식회사 Method and apparatus for measuring concentration of constituents in body fluids
EP1628567B1 (en) 2003-05-30 2010-08-04 Pelikan Technologies Inc. Method and apparatus for fluid injection
DK1633235T3 (en) 2003-06-06 2014-08-18 Sanofi Aventis Deutschland Apparatus for sampling body fluid and detecting analyte
WO2006001797A1 (en) 2004-06-14 2006-01-05 Pelikan Technologies, Inc. Low pain penetrating
US8282576B2 (en) 2003-09-29 2012-10-09 Sanofi-Aventis Deutschland Gmbh Method and apparatus for an improved sample capture device
EP1680014A4 (en) 2003-10-14 2009-01-21 Pelikan Technologies Inc Method and apparatus for a variable user interface
JP2005192611A (en) * 2003-12-26 2005-07-21 Olympus Corp Glucose concentration measuring apparatus
US7822454B1 (en) 2005-01-03 2010-10-26 Pelikan Technologies, Inc. Fluid sampling device with improved analyte detecting member configuration
EP1706026B1 (en) 2003-12-31 2017-03-01 Sanofi-Aventis Deutschland GmbH Method and apparatus for improving fluidic flow and sample capture
US8828203B2 (en) 2004-05-20 2014-09-09 Sanofi-Aventis Deutschland Gmbh Printable hydrogels for biosensors
EP1765194A4 (en) 2004-06-03 2010-09-29 Pelikan Technologies Inc Method and apparatus for a fluid sampling device
US9775553B2 (en) 2004-06-03 2017-10-03 Sanofi-Aventis Deutschland Gmbh Method and apparatus for a fluid sampling device
US8652831B2 (en) 2004-12-30 2014-02-18 Sanofi-Aventis Deutschland Gmbh Method and apparatus for analyte measurement test time
US7341330B2 (en) 2005-02-28 2008-03-11 Silverbrook Research Pty Ltd Substrates adapted for adhesive bonding
WO2006089337A1 (en) * 2005-02-28 2006-08-31 Silverbrook Research Pty Ltd Method of bonding substrates
US7425052B2 (en) * 2005-02-28 2008-09-16 Silverbrook Research Pty Ltd Printhead assembly having improved adhesive bond strength
US7468284B2 (en) * 2005-02-28 2008-12-23 Silverbrook Research Pty Ltd Method of bonding substrates
US7287831B2 (en) * 2005-02-28 2007-10-30 Silverbrook Research Pty Ltd Printhead integrated circuit adapted for adhesive bonding
US7372145B2 (en) * 2005-02-28 2008-05-13 Silverbrook Research Pty Ltd Bonded assembly having improved adhesive bond strength
WO2006113476A2 (en) * 2005-04-15 2006-10-26 Bayer Healthcare Llc Non-invasive system for measuring glucose in the body
GB0606891D0 (en) * 2006-04-05 2006-05-17 Council Cent Lab Res Councils Raman Analysis Of Pharmaceutical Tablets
JP3992064B2 (en) * 2006-01-20 2007-10-17 住友電気工業株式会社 Optical analyzer
JP4928849B2 (en) * 2006-06-27 2012-05-09 東芝メディカルシステムズ株式会社 Non-invasive measuring device
US7973925B2 (en) * 2007-02-06 2011-07-05 C8 Medisensors Inc. Apparatus for stabilizing mechanical, thermal, and optical properties and for reducing the fluorescence of biological samples for optical evaluation
US7782191B2 (en) * 2007-07-25 2010-08-24 Tomas Flores Portable alarm apparatus for warning persons
CN104777291B (en) * 2007-10-10 2017-09-12 普凯尔德诊断技术有限公司 System for identifying bacterium in urine
CN110967298A (en) * 2008-02-05 2020-04-07 普凯尔德诊断技术有限公司 System for identifying bacteria in biological samples
JP4914388B2 (en) * 2008-03-07 2012-04-11 日本電信電話株式会社 Component concentration measuring device
WO2009126900A1 (en) 2008-04-11 2009-10-15 Pelikan Technologies, Inc. Method and apparatus for analyte detecting device
US20110160555A1 (en) * 2008-07-31 2011-06-30 Jacques Reifman Universal Models for Predicting Glucose Concentration in Humans
US7959598B2 (en) 2008-08-20 2011-06-14 Asante Solutions, Inc. Infusion pump systems and methods
US9375169B2 (en) 2009-01-30 2016-06-28 Sanofi-Aventis Deutschland Gmbh Cam drive for managing disposable penetrating member actions with a single motor and motor and control system
US8309897B2 (en) * 2009-02-06 2012-11-13 Pocared Diagnostics Ltd. Optical measurement arrangement
US10288632B2 (en) * 2009-09-21 2019-05-14 Pocared Diagnostics Ltd. System for conducting the identification of bacteria in biological samples
US8965476B2 (en) 2010-04-16 2015-02-24 Sanofi-Aventis Deutschland Gmbh Tissue penetration device
US20110313680A1 (en) * 2010-06-22 2011-12-22 Doyle Iii Francis J Health Monitoring System
US8804114B2 (en) 2010-11-03 2014-08-12 Pocared Diagnostics Ltd. Optical cup
US8411265B2 (en) 2011-06-14 2013-04-02 C8 Medisensors Inc. Apparatus for stabilizing mechanical, thermal, and optical properties and for reducing the fluorescence of biological samples for optical evaluation
JP5426644B2 (en) * 2011-12-06 2014-02-26 東芝メディカルシステムズ株式会社 Non-invasive measuring device
US9766126B2 (en) 2013-07-12 2017-09-19 Zyomed Corp. Dynamic radially controlled light input to a noninvasive analyzer apparatus and method of use thereof
US9351671B2 (en) 2012-07-16 2016-05-31 Timothy Ruchti Multiplexed pathlength resolved noninvasive analyzer apparatus and method of use thereof
US9585604B2 (en) * 2012-07-16 2017-03-07 Zyomed Corp. Multiplexed pathlength resolved noninvasive analyzer apparatus with dynamic optical paths and method of use thereof
US9351672B2 (en) 2012-07-16 2016-05-31 Timothy Ruchti Multiplexed pathlength resolved noninvasive analyzer apparatus with stacked filters and method of use thereof
US9065554B2 (en) * 2012-08-01 2015-06-23 Comcast Cable Communications, Llc System and method for analyzing a network
US20140058224A1 (en) * 2012-08-21 2014-02-27 Opticks, Inc. Systems and methods for detection of carotenoid-related compounds in biological tissue
US10067054B2 (en) 2012-10-16 2018-09-04 K Sciences Gp, Llc Simple sugar concentration sensor and method
US8743355B2 (en) 2012-10-16 2014-06-03 K Sciences Gp, Llc Simple sugar concentration sensor and method
US9862920B2 (en) 2012-12-11 2018-01-09 Pocared Diagnostics Ltd. Optics cup with curved bottom
US10395134B2 (en) * 2013-07-26 2019-08-27 University Of Utah Research Foundation Extraction of spectral information
GB2523989B (en) 2014-01-30 2020-07-29 Insulet Netherlands B V Therapeutic product delivery system and method of pairing
DE102014108424B3 (en) 2014-06-16 2015-06-11 Johann Wolfgang Goethe-Universität Non-invasive substance analysis
CN104200090B (en) * 2014-08-27 2017-07-14 百度在线网络技术(北京)有限公司 Forecasting Methodology and device based on multi-source heterogeneous data
US9459201B2 (en) 2014-09-29 2016-10-04 Zyomed Corp. Systems and methods for noninvasive blood glucose and other analyte detection and measurement using collision computing
WO2016069909A1 (en) * 2014-10-29 2016-05-06 Zoll Medical Corporation Transesophageal or transtracheal cardiac monitoring by optical spectroscopy
US10737024B2 (en) 2015-02-18 2020-08-11 Insulet Corporation Fluid delivery and infusion devices, and methods of use thereof
GB2555229B (en) * 2015-03-05 2021-03-24 Synaptive Medical Inc An optical coherence tomography system including a planarizing transparent material
CN105319181A (en) * 2015-11-02 2016-02-10 南京航空航天大学 Biological tissue thermal damage parameter measurement method
US11426100B1 (en) 2015-12-08 2022-08-30 Socrates Health Solutions, Inc. Blood glucose trend meter
US11280728B2 (en) 2015-12-09 2022-03-22 Diamontech Ag Device and method for analyzing a material
CN108369182B (en) 2015-12-09 2021-10-15 迪亚蒙泰克股份有限公司 Device and method for analyzing materials
WO2017123525A1 (en) 2016-01-13 2017-07-20 Bigfoot Biomedical, Inc. User interface for diabetes management system
EP3453414A1 (en) 2016-01-14 2019-03-13 Bigfoot Biomedical, Inc. Adjusting insulin delivery rates
US9554738B1 (en) 2016-03-30 2017-01-31 Zyomed Corp. Spectroscopic tomography systems and methods for noninvasive detection and measurement of analytes using collision computing
EP3515535A1 (en) 2016-09-23 2019-07-31 Insulet Corporation Fluid delivery device with sensor
KR20180050946A (en) * 2016-11-07 2018-05-16 삼성전자주식회사 Apparatus and method for providing health state of cardiovascular system
KR102515832B1 (en) * 2017-03-27 2023-03-29 삼성전자주식회사 Glucose feature extraction method, Glucose monitoring apparatus and method
EP3381368A1 (en) * 2017-03-27 2018-10-03 Samsung Electronics Co., Ltd. Method of enabling feature extraction for glucose monitoring using near-infrared (nir) spectroscopy
WO2019019119A1 (en) * 2017-07-27 2019-01-31 Vita-Course Technologies (Hainan) Co., Ltd. Systems and methods for determining blood pressure of subject
KR102487058B1 (en) 2017-11-17 2023-01-09 삼성전자주식회사 Apparatus and method for measuring bio-information
US11504070B2 (en) 2018-02-23 2022-11-22 Samsung Electronics Co., Ltd. Apparatus and method for estimation concentration of blood compound
USD928199S1 (en) 2018-04-02 2021-08-17 Bigfoot Biomedical, Inc. Medication delivery device with icons
CN112236826A (en) 2018-05-04 2021-01-15 英赛罗公司 Safety constraints for drug delivery systems based on control algorithms
CA3112209C (en) 2018-09-28 2023-08-29 Insulet Corporation Activity mode for artificial pancreas system
US11565039B2 (en) 2018-10-11 2023-01-31 Insulet Corporation Event detection for drug delivery system
US11744491B2 (en) * 2019-05-14 2023-09-05 The Regents Of The University Of California Noninvasive method and apparatus for peripheral assessment of vascular health
US11801344B2 (en) 2019-09-13 2023-10-31 Insulet Corporation Blood glucose rate of change modulation of meal and correction insulin bolus quantity
US11935637B2 (en) 2019-09-27 2024-03-19 Insulet Corporation Onboarding and total daily insulin adaptivity
US11833329B2 (en) 2019-12-20 2023-12-05 Insulet Corporation Techniques for improved automatic drug delivery performance using delivery tendencies from past delivery history and use patterns
US11551802B2 (en) 2020-02-11 2023-01-10 Insulet Corporation Early meal detection and calorie intake detection
US11547800B2 (en) 2020-02-12 2023-01-10 Insulet Corporation User parameter dependent cost function for personalized reduction of hypoglycemia and/or hyperglycemia in a closed loop artificial pancreas system
US11324889B2 (en) 2020-02-14 2022-05-10 Insulet Corporation Compensation for missing readings from a glucose monitor in an automated insulin delivery system
US11607493B2 (en) 2020-04-06 2023-03-21 Insulet Corporation Initial total daily insulin setting for user onboarding
US11684716B2 (en) 2020-07-31 2023-06-27 Insulet Corporation Techniques to reduce risk of occlusions in drug delivery systems
US11904140B2 (en) 2021-03-10 2024-02-20 Insulet Corporation Adaptable asymmetric medicament cost component in a control system for medicament delivery
WO2023049900A1 (en) 2021-09-27 2023-03-30 Insulet Corporation Techniques enabling adaptation of parameters in aid systems by user input
US11439754B1 (en) 2021-12-01 2022-09-13 Insulet Corporation Optimizing embedded formulations for drug delivery

Family Cites Families (50)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4526568A (en) * 1982-09-29 1985-07-02 Miles Laboratories, Inc. Diagnostic method and apparatus for clamping blood glucose concentration
US5137023A (en) * 1990-04-19 1992-08-11 Worcester Polytechnic Institute Method and apparatus for monitoring blood analytes noninvasively by pulsatile photoplethysmography
US5178142A (en) * 1989-05-23 1993-01-12 Vivascan Corporation Electromagnetic method and apparatus to measure constituents of human or animal tissue
US5183042A (en) * 1989-05-23 1993-02-02 Vivascan Corporation Electromagnetic method and apparatus to measure constituents of human or animal tissue
EP0401453B1 (en) * 1989-05-23 1992-09-02 Biosensors Technology, Inc. Method for determining by absorption of radiations the concentration of substances in absorbing and turbid matrices
US4975581A (en) * 1989-06-21 1990-12-04 University Of New Mexico Method of and apparatus for determining the similarity of a biological analyte from a model constructed from known biological fluids
US5039855A (en) * 1990-03-05 1991-08-13 Bran+Luebbe Analyzing Technologies, Inc. Dual beam acousto-optic tunable spectrometer
US5120961A (en) 1990-03-16 1992-06-09 Infrared Fiber Systems, Inc. High sensitivity acousto-optic tunable filter spectrometer
US5115133A (en) * 1990-04-19 1992-05-19 Inomet, Inc. Testing of body fluid constituents through measuring light reflected from tympanic membrane
US5090418A (en) * 1990-11-09 1992-02-25 Del Mar Avionics Method and apparatus for screening electrocardiographic (ECG) data
WO1993012712A1 (en) * 1991-12-31 1993-07-08 Vivascan Corporation Blood constituent determination based on differential spectral analysis
US5370114A (en) * 1992-03-12 1994-12-06 Wong; Jacob Y. Non-invasive blood chemistry measurement by stimulated infrared relaxation emission
US6222189B1 (en) * 1992-07-15 2001-04-24 Optix, Lp Methods of enhancing optical signals by mechanical manipulation in non-invasive testing
US5348003A (en) * 1992-09-03 1994-09-20 Sirraya, Inc. Method and apparatus for chemical analysis
US6172743B1 (en) * 1992-10-07 2001-01-09 Chemtrix, Inc. Technique for measuring a blood analyte by non-invasive spectrometry in living tissue
US5435309A (en) * 1993-08-10 1995-07-25 Thomas; Edward V. Systematic wavelength selection for improved multivariate spectral analysis
CA2174719C (en) * 1993-08-24 2005-07-26 Mark R. Robinson A robust accurate non-invasive analyte monitor
US5459317A (en) * 1994-02-14 1995-10-17 Ohio University Method and apparatus for non-invasive detection of physiological chemicals, particularly glucose
US5560356A (en) * 1994-02-23 1996-10-01 Vitrophage, Inc. Diagnostic system and method using an implanted reflective device
TW275570B (en) * 1994-05-05 1996-05-11 Boehringer Mannheim Gmbh
US5477321A (en) * 1994-08-31 1995-12-19 Bayer Corporation Dual beam tunable spectrometer
US5571401A (en) * 1995-03-27 1996-11-05 California Institute Of Technology Sensor arrays for detecting analytes in fluids
SG38866A1 (en) * 1995-07-31 1997-04-17 Instrumentation Metrics Inc Liquid correlation spectrometry
US5606164A (en) * 1996-01-16 1997-02-25 Boehringer Mannheim Corporation Method and apparatus for biological fluid analyte concentration measurement using generalized distance outlier detection
US5655530A (en) * 1995-08-09 1997-08-12 Rio Grande Medical Technologies, Inc. Method for non-invasive blood analyte measurement with improved optical interface
US5636633A (en) * 1995-08-09 1997-06-10 Rio Grande Medical Technologies, Inc. Diffuse reflectance monitoring apparatus
US6174424B1 (en) * 1995-11-20 2001-01-16 Cirrex Corp. Couplers for optical fibers
EP0889703B1 (en) * 1996-02-05 2001-11-21 Diasense, Inc. Apparatus for non-invasive glucose sensing
ATE346539T1 (en) * 1996-07-19 2006-12-15 Daedalus I Llc DEVICE FOR THE BLOODLESS DETERMINATION OF BLOOD VALUES
EP1011426A1 (en) * 1997-02-26 2000-06-28 Diasense, Inc. Individual calibration of blood glucose for supporting noninvasive self-monitoring blood glucose
TW352335B (en) * 1997-03-25 1999-02-11 Matsushita Electric Works Ltd Method of determining a glucose concentration in a target by using near-infrared spectroscopy
JP3758823B2 (en) * 1997-08-06 2006-03-22 倉敷紡績株式会社 Biological positioning device
US6558351B1 (en) * 1999-06-03 2003-05-06 Medtronic Minimed, Inc. Closed loop system for controlling insulin infusion
US5815277A (en) 1997-06-20 1998-09-29 The Board Of Trustees Of The Leland Stanford Junior Univesity Deflecting light into resonant cavities for spectroscopy
GB2328279B (en) * 1997-08-12 2001-10-10 Abbott Lab Optical glucose detector
US6070093A (en) * 1997-12-02 2000-05-30 Abbott Laboratories Multiplex sensor and method of use
US6119026A (en) * 1997-12-04 2000-09-12 Hewlett-Packard Company Radiation apparatus and method for analysis of analytes in sample
US6721582B2 (en) 1999-04-06 2004-04-13 Argose, Inc. Non-invasive tissue glucose level monitoring
US6241663B1 (en) * 1998-05-18 2001-06-05 Abbott Laboratories Method for improving non-invasive determination of the concentration of analytes in a biological sample
US6662030B2 (en) 1998-05-18 2003-12-09 Abbott Laboratories Non-invasive sensor having controllable temperature feature
US6064897A (en) * 1998-06-01 2000-05-16 Abbott Laboratories Sensor utilizing Raman spectroscopy for non-invasive monitoring of analytes in biological fluid and method of use
US6441388B1 (en) * 1998-10-13 2002-08-27 Rio Grande Medical Technologies, Inc. Methods and apparatus for spectroscopic calibration model transfer
US6157041A (en) * 1998-10-13 2000-12-05 Rio Grande Medical Technologies, Inc. Methods and apparatus for tailoring spectroscopic calibration models
JP2000186998A (en) 1998-12-22 2000-07-04 Matsushita Electric Works Ltd Living body spectrum measuring device
US6725073B1 (en) * 1999-08-17 2004-04-20 Board Of Regents, The University Of Texas System Methods for noninvasive analyte sensing
IL135077A0 (en) * 2000-03-15 2001-05-20 Orsense Ltd A probe for use in non-invasive measurements of blood related parameters
US6862091B2 (en) 2001-04-11 2005-03-01 Inlight Solutions, Inc. Illumination device and method for spectroscopic analysis
US7308293B2 (en) * 2001-08-02 2007-12-11 Glucovista, Llc Non-invasive glucose meter
CA2418399A1 (en) 2002-02-11 2003-08-11 Bayer Healthcare, Llc Non-invasive system for the determination of analytes in body fluids
JP2007518443A (en) 2003-07-09 2007-07-12 グルコン インク Wearable glucometer

Also Published As

Publication number Publication date
US20080045821A1 (en) 2008-02-21
US9554735B2 (en) 2017-01-31
AU2003200359A1 (en) 2003-08-28
EP1335199A1 (en) 2003-08-13
US20130261406A1 (en) 2013-10-03
US20080045820A1 (en) 2008-02-21
US8452359B2 (en) 2013-05-28
JP4476552B2 (en) 2010-06-09
EP2400288A1 (en) 2011-12-28
US7299079B2 (en) 2007-11-20
US20040092804A1 (en) 2004-05-13
JP2003235832A (en) 2003-08-26
US8160666B2 (en) 2012-04-17

Similar Documents

Publication Publication Date Title
US9554735B2 (en) Method for building an algorithm for converting spectral information
US8180422B2 (en) Non-invasive system and method for measuring an analyte in the body
US7254432B2 (en) Method and device for non-invasive measurements of blood parameters
US5553615A (en) Method and apparatus for noninvasive prediction of hematocrit
US5460177A (en) Method for non-invasive measurement of concentration of analytes in blood using continuous spectrum radiation
US5372135A (en) Blood constituent determination based on differential spectral analysis
US5383452A (en) Method, apparatus and procedure for non-invasive monitoring blood glucose by measuring the polarization ratio of blood luminescence
EP0919180B1 (en) Method and apparatus for noninvasive measurement of blood glucose by photoacoustics
US8552359B2 (en) Optical spectroscopy device for non-invasive blood glucose detection and associated method of use
US20070078312A1 (en) Method and system for non-invasive measurements in a human body
US20040167382A1 (en) Non-invasive determination of direction and rate of change of an analyte
CA2310468A1 (en) Multiplex sensor and method of use
EP1885235A1 (en) Improved method for spectrophotometric blood oxygenation monitoring
CN105249974A (en) Pressure-modulation-spectrum-technology-based noninvasive glucose detection system and method
US20060063991A1 (en) Method and apparatus for non-invasive measurement of blood analytes with dynamic spectral calibration
WO1999043255A1 (en) Near infrared-transmission spectroscopy of tongue tissue
JP3694291B2 (en) Blood glucose level non-invasive measurement device
Araujo-Andrade et al. Non-invasive in-vivo blood glucose levels prediction using near infrared spectroscopy
GB2613032A (en) Calibration method and system
CA2146856C (en) Method and apparatus for non-invasive measurement of blood sugar level
Shih et al. Introduction to spectroscopy for noninvasive glucose sensing

Legal Events

Date Code Title Description
EEER Examination request
FZDE Discontinued
FZDE Discontinued

Effective date: 20120423