Method for determining current glucose level in delivered fluid

Abstract

The invention relates to a method, in particular a method for continuously determining a current glucose value in a transport fluid, in particular in the blood, of a biological subject, the method comprising the following steps: a) determining a measurement value sequence comprising at least two measurement values ​​separated by a time interval for a tissue glucose value in tissue surrounding the transport fluid using a sensor device; b) determining the tissue glucose value using the determined measurement value sequence based on a sensor model, wherein the measured values ​​of the sensor device are correlated with the tissue glucose value using the sensor model while taking into account measurement noise; c) providing a state transition model, correlating the determined tissue glucose value with at least one glucose value in the transport fluid using the state transition model while taking into account process noise; and d) determining the current glucose value based on the provided state transition model and the determined tissue glucose value. At least step d), in particular steps b)-d), are performed using at least one rolling time domain estimation method.

Description

Technical Field

[0001] The invention relates to a method for preferably continuously determining the current glucose level in a transport fluid, in particular in the blood, of a living being.

[0002] The invention further relates to a device for determining, preferably continuously, the current glucose level in a transport fluid, in particular in the blood, of a living being.

[0003] The invention further relates to an evaluation device for determining, preferably continuously, the current glucose level in a transport fluid, in particular in the blood, of a living being.

[0004] The invention also relates to an intangible machine-readable medium for storing instructions which, when executed on a computer, cause the execution of a method for determining, preferably continuously, a current glucose level in a transport fluid, in particular in the blood, of a biological subject.

[0005] Although the present invention is generally applicable to any method for determining the current glucose level in a delivered fluid, the invention will be described with reference to blood glucose concentration in a living organism. Background Art

[0006] In order to determine the blood glucose concentration BG in an organism, in particular in a human body, a system for continuous glucose monitoring, also known as CGM (continuous glucose monitoring) is known. In a CGM system, the interstitial tissue glucose concentration IG is usually automated, for example, measured once every one to five minutes. In particular, diabetic patients benefit from CGM systems because measurements can be performed at a significantly higher frequency compared to the self-monitoring process (also known as Self Monitoring Processes) in which the patient himself manually determines the blood glucose level four to ten times a day. This allows automatic evaluation and warning signals to be provided to the patient, especially even when the patient is asleep, which helps prevent the patient's critical health condition.

[0007] On the one hand, known CGM systems are based on electrochemical processes. Such a CGM system is described, for example, in WO 2006 / 017358 A1. In addition, optical CGM systems are known, for example, from DE 10 2015 101 847 B4, in which fluorescence dependent on glucose levels is used, and this document is hereby incorporated by reference. Both CGM systems measure interstitial tissue glucose concentration.

[0008] Furthermore, it is known that tissue glucose concentration or interstitial glucose (IG) concentration deviates from the blood glucose concentration, hereinafter referred to as BG. In particular, after a strong influence on the blood glucose level, for example by the intake of food or nutrients or the supply of insulin, there will be a large deviation, as described in the non-patent document "Time lag of Glucose from intravascular to interstitial compartment in humans." by Basu, Ananda et al. (Diabetes (2013): DB-131132). This deviation is caused by diffusion processes in the tissues surrounding the blood, which causes IG levels to be delayed in time and follow BG levels in an unclear manner, for example, as described in the non-patent document "Subcutaneous Glucose predicts plasma Glucose independent of insulin: implications for continuous monitoring" by Rebrin, Kerstin et al. (American Journal of Physiology-Endocrinology and Metabolism 277.3 (1999): E561-E571).

[0009] Calibration of CGM systems by manual determination of blood glucose concentration (e.g. by drawing a drop of blood from a finger and using an external measuring device to determine the glucose concentration in the blood drop) can lead to significant inaccuracies due to muffling and time delay between the two glucose concentrations in the blood BG on the one hand and in the peripheral tissue (IG) on the other hand.

[0010] However, in order to achieve accurate calibration of the CGM system, the above-mentioned difference between tissue glucose concentration and blood glucose concentration must be considered or at least evaluated. To this end, various methods are known. According to the non-patent literature "Delays in minimally invasive continuous Glucose monitoring devices: a review of current technology" (Journal of Diabetes Science and Technology 3.5 (2009): 1207-1214) by Keenan, D.Barry et al., it is known to use a time-delayed glucose signal for calibration. In addition, according to the non-patent literature "The extended Kalman filter for continuous Glukose monitoring" (Diabetes Technology & Therapeutics 7.1 (2005): 15-27) by Knobbe, Edward J. and Bruce Buckingham, it is known how to use a Kalman filter to compensate for the inhibition (muffling) and time delay of the glucose diffusion process between blood and tissue. Summary of the invention

[0011] Therefore, the object of the present invention is to provide an apparatus and an evaluation device which enable a more accurate determination of glucose levels, in particular in the blood, with greater flexibility, in particular taking into account additional parameters and a simpler implementation. Another object of the present invention is to provide an alternative method, an alternative apparatus and an alternative evaluation device. Another object of the present invention is to provide a method, an apparatus and an evaluation device which allow a better determination of the blood glucose concentration in an organism based on the measurement of interstitial tissue glucose levels.

[0012] In one embodiment, the present invention achieves the above object by a method for preferably continuously determining the current glucose level in a transport fluid, in particular in the blood, of a living being, the method comprising the following steps:

[0013] a) determining a series of measurements in tissue surrounding the transport fluid using the sensor device, including at least two temporally separated measurements of tissue glucose levels,

[0014] b) determining the tissue glucose level using the given series of measured values ​​based on a sensor model, wherein the measured values ​​of the sensor device are correlated with the tissue glucose level by means of the sensor model while taking into account the measurement noise

[0015] c) providing a state transition model, wherein by means of the state transition model at least one glucose level in the transport fluid is related to the determined tissue glucose level while taking into account process noise, and

[0016] d) determining a current glucose level based on the provided state transition model and the determined tissue glucose level,

[0017] Therein, at least step d), in particular steps b)-d) are performed using at least one moving horizon estimation method.

[0018] In another embodiment, the invention achieves the above objects by a device for preferably continuously determining the current glucose level in a transport fluid, in particular in the blood, of a living being, said device preferably being adapted to carry out the method according to the invention, said device comprising

[0019] A sensor device, in particular for measuring fluorescence in tissue surrounding a transport fluid by means of a fiber optic probe, the sensor device being designed to determine a series of measurement values, including at least two measurement values ​​separated in time for the tissue surrounding the transport fluid,

[0020] A device is provided, which is designed to provide a state transition model and to provide a sensor model, wherein by means of the state transition model at least one glucose level in the transport fluid is correlated with the determined tissue glucose level while taking into account process noise, wherein by means of the sensor model the measured values ​​of the sensor device are correlated with the tissue glucose level while taking into account measurement noise,

[0021] An evaluation device is designed to determine a tissue glucose level based on a sensor model using a provided series of measurement values, and to determine a current glucose level based on the provided state transition model and the determined tissue glucose level using a rolling horizon estimation method.

[0022] In another embodiment, the invention achieves the above object by an evaluation device for preferably continuously determining the current glucose level in a transport fluid, in particular in the blood, of a living being, preferably adapted to perform the method according to the invention, said evaluation device comprising:

[0023] at least one interface for connecting a sensor device to provide a series of measurements, including at least two temporally separated measurements of glucose levels of tissue surrounding the transport fluid,

[0024] at least one memory for storing a state transition model and for storing a sensor model, wherein at least one glucose level in the transport fluid is correlated to the tissue glucose level by means of the state transition model while taking into account at least one process noise level, wherein the measured values ​​of the sensor device are correlated to the tissue glucose level by means of the sensor model while taking into account at least one measurement noise, and

[0025] A computing device is designed to determine a tissue glucose level based on a sensor model using a provided series of measurements, and to determine a current glucose level based on a stored state transition model and the determined tissue glucose level using at least one rolling horizon estimation method.

[0026] In another embodiment, the present invention achieves the above objects by an intangible machine-readable medium for storing instructions which, when executed on a computer, perform a method preferably adapted to perform the method according to the present invention, in particular to continuously determine the current glucose level in a transport fluid, in particular in the blood, of a biological subject, said method comprising the steps of:

[0027] a) determining a series of measurements in tissue surrounding the transport fluid using the sensor device, including at least two temporally separated measurements of tissue glucose levels,

[0028] b) determining the tissue glucose level using the given series of measured values ​​based on a sensor model, wherein the measured values ​​of the sensor device are correlated with the tissue glucose level by means of the sensor model while taking into account measurement noise,

[0029] c) providing a state transition model, wherein by means of the state transition model at least one glucose level in the transport fluid is related to the determined tissue glucose level while taking into account process noise, and

[0030] d) determining a current glucose level based on the provided state transition model and the determined tissue glucose level,

[0031] Therein, at least step d), in particular steps b)-d) are performed using at least one moving horizon estimation method.

[0032] In other words, a method for determining the blood glucose concentration in an organism is proposed. The method presents the following method steps:

[0033] In a first method step, a series of measurements of the tissue glucose level of a tissue of a living body is present by means of a sensor, the measurement having at least two sensor measurements spaced apart in time. In a further step, a sensor model is provided for the association between the sensor measurements and the tissue glucose level, and a state transition model is provided, the state transition model comprising a model for the association between the tissue glucose level and the blood glucose value, and in a further method step, there is a quantification of the blood glucose level of the living body by means of the sensor model and the state transition model associated with the sensor measurements, wherein the use of a rolling horizon estimation method is necessary.

[0034] The method of rolling horizon estimation (MHE for short) is known in principle for evaluating a measurement signal present as a series of statistical values. Studies by the applicant have shown that, in contrast to the methods used hitherto, the use of a rolling horizon estimation method provides significant advantages for the evaluation of sensor measurement values ​​for quantifying blood glucose levels in terms of the accuracy of the estimation and in terms of the flexibility associated with the assumptions of the model and in terms of the speed at which the blood glucose level is provided, in contrast to the methods used hitherto. Preferably, the rolling horizon estimation method generates a current blood glucose concentration and a retrospective blood glucose concentration, wherein the retrospective blood glucose concentration is preferably determined taking into account at least one previous blood glucose concentration (a blood glucose concentration previously determined in a measurement process (concentration process)). As a result, the retrospective blood glucose concentration makes it possible in particular to better reconstruct the current blood glucose measurement signal only as the current blood glucose concentration.

[0035] Here, the evaluation device can be a computer, an integrated circuit or a similar device that is, for example, specially constructed for the optimization calculation of the trace of a matrix. According to one embodiment of the present invention, the device and / or the evaluation device can be designed as a portable device that allows efficient operation with an independent energy source, such as a battery or the like, and thereby also keeps the energy consumption for executing the method as low as possible so that the battery can be operated for as long as possible, which enhances the user experience. For this purpose, energy-saving processors, wiring, circuits, interfaces, in particular wireless interfaces, etc. can be used in particular. Here, the execution of the method can be matched in terms of its parameters, for example, with the following device, such as the evaluation device in the evaluation time domain and / or the noise time domain (this case is described later) in order to achieve sufficient accuracy on the one hand and a longer running time on the other hand.

[0036] One of the advantages obtained is that a higher efficiency is provided for the estimation of the current glucose level in the transported fluid, in particular in the blood, in terms of time and computing resources. Furthermore, there is the advantage of significantly increased flexibility compared to known methods, since the restrictions on certain sensor models and / or state transition models are eliminated. Another advantage is that not only the accuracy of the current glucose level is increased, but also the previous glucose level is improved at the same time.

[0037] Other features, advantages, and embodiments of the invention are described below or disclosed therein.

[0038] According to a preferred embodiment, a rolling horizon estimation method is performed to provide a current glucose level in step d) and is applied to previously provided glucose measurements and at least one previous tissue glucose measurement. In particular, this provides an efficient determination of the current glucose level based on the glucose levels of the previous measurements.

[0039] According to another preferred embodiment, the sensor model is provided in the form of a linear function between measured values ​​and tissue glucose level. This allows a particularly efficient and fast calculation of the interstitial tissue glucose level based on the measured values ​​of a series of measured values ​​simultaneously with sufficient accuracy.

[0040] According to another preferred embodiment, the sensor model is provided in the form of a nonlinear function between the measured value and the tissue glucose level. Here, for example, the following sensor model can be provided, where y represents the measured value, IG represents the glucose concentration, and a, b, c or A, b, c represents the sensor parameters:

[0041] y=ca*b / (IG+b)

[0042] Alternatively, the following nonlinear sensor model could be:

[0043] y=(A*b+C*IG) / (IG+b)

[0044] This has the advantage that the interstitial tissue glucose level calculated based on the measured values ​​of a series of measured values, in particular by means of a sensor device with an affinity binding sensor or an optical sensor, has a higher precision.

[0045] According to another preferred embodiment of the invention, the value of the time domain of the method for providing the rolling time domain estimate of the current glucose level is selected to be less than or equal to 10. This enables a particularly efficient and rapid calculation of the interstitial tissue glucose level based on the measured values ​​of a series of measured values ​​simultaneously with sufficient accuracy.

[0046] According to a further preferred embodiment, the variance of the measurement noise and / or process noise is estimated, in particular at least regularly. This allows a simple and rapid provision of noise measurement values ​​and thus overall a precise determination of the current glucose level.

[0047] According to another preferred embodiment, the variance of the measurement noise and / or the variance of the process noise is estimated or in particular interpolated and / or weighted, preferably using exponential smoothing. In this case, any noise level that changes over time can be matched or updated, which further improves the overall accuracy of determining the current glucose level.

[0048] According to a further preferred embodiment, measured values ​​which are only partially used for calculating an estimate of the measurement noise and / or process noise can be temporarily stored, and the stored measurements can be used to interpolate the required measured values ​​which have not yet been temporarily stored. Thus, for example, for the determination of the measurement noise level and / or the process noise level, necessary and computationally intensive measured values ​​can be at least partially temporarily stored and made available for subsequent measurements, which overall reduces the amount of calculations required for determining the current glucose level without significantly reducing its accuracy.

[0049] According to another preferred embodiment, some previous measurement values ​​are selected, which are larger than the measurement values ​​of the time domain of the rolling time domain estimation method, in particular at least twice as large, preferably at least 5 times as large, so as to determine the accuracy of the estimate of the process noise and / or measurement noise associated with the current glucose level and improve the overall accuracy of the determination or quantification of the current glucose level.

[0050] According to another preferred embodiment, the variance of the measurement noise and / or the variance of the process noise is regularly adjusted based on the level of the sum of the time domain of the rolling horizon estimation method and the number of previous measurements used for calculating the estimate of the measurement noise and / or process noise. This ensures that an efficient adjustment of the noise measurement at any given time will be performed at regular intervals, on the one hand, in order to achieve a sufficient accuracy of the current glucose level and on the other hand, in order to prevent unnecessary adjustments or updates, which do not lead to an increase in the accuracy of the current glucose level or do not lead to a significant increase thereof.

[0051] According to a further preferred embodiment, the provided measured values ​​are filtered by means of a filter function, whereby errors, in particular measurement errors, are suppressed by the sensor device by means of the filter function. With the aid of the filter function, erroneous measured values, such as sensor errors or outliers in the measured values, can be simply picked out; this means that these erroneous measured values ​​are not taken into account in the further calculation of the current glucose level.

[0052] According to another preferred embodiment, the measurement noise measured values ​​are weighted by means of a filter function. This prevents underestimation and overestimation of the measurement noise level: underestimation leads to extremely erroneous signals or measured values, while overestimation leads to an overly smooth measurement process for a series of measured values. Overall, this further improves the accuracy.

[0053] According to another preferred embodiment, in order to determine the error of the sensor device, the current tissue glucose level and / or the gradient of the increase of the current tissue glucose level is evaluated. Alternatively or additionally, this can also be performed by the gradient of the increase of the current glucose level and / or the current glucose level of its delivery fluid. This provides a simple and at the same time reliable and efficient error identification of the sensor device.

[0054] According to a further preferred embodiment, measured values ​​provided below a predeterminable low threshold level and / or above a predeterminable high threshold level are filtered out by means of a filter function, in particular, the low threshold level and the high threshold level correspond to physiological limits, preferably, wherein the low threshold level assumes a value between 10-50 mg / dL, in particular 30 mg / dL, and the high threshold level assumes a value between 100-600 mg / dL, preferably 450 mg / dL. By means of appropriate threshold levels, erroneous sensor measured values ​​are advantageously filtered out for further calculations by means of a weighting matrix, preferably a diagonal weighting matrix, erroneous sensor measured values, including glucose measured values ​​in the transport fluid, in particular in the blood, and tissue glucose measured values. Advantageously, the weighting matrix functions in such a way that erroneous measured values ​​of the sensor device can be weighted with a factor of 0, while all other measurements are weighted with a factor of 1. Erroneous measured values, for example outliers in the sensor measurements, are determined by the absolute glucose concentration in the transport fluid, in particular in the blood, and its rate of change or its gradient. In the first case described, preferably physiological limits for blood glucose concentration are introduced, wherein a blood glucose concentration range of 10 mg / dL-600 mg / dL, preferably 20 mg / dL-500 mg / dL, most preferably 30 mg / dL-450 mg / dL is assumed. Measurement values ​​outside these physiological limits are weighted as erroneous sensor measurement values ​​with a factor of 0. Likewise, the gradient of the glucose concentration in the transport fluid, in particular in the blood, or the rate of change of the glucose concentration in the transport fluid, in particular in the blood, can be determined and its level can be compared with the physiologically actual rate of change. Thus, the quantified rate of change of the glucose concentration in the transport fluid, in particular in the blood, is a value from 0.1 mg / dL per minute to 15 mg / dL per minute, preferably from 0.5 mg / dL per minute to 10 mg / dL per minute, most preferably from 1 mg / dL per minute to 3 mg / dL per minute.

[0055] According to another preferred embodiment, calibration of the measured values ​​of the sensor device is performed after performing step d). Thus, uncalibrated tissue glucose measurements can be used, which has the advantage that calibration does not have to be performed before performing the rolling time domain estimation method, but can also be performed after the rolling time domain estimation method. Another advantage of using uncalibrated tissue glucose measurements is that uncalibrated tissue glucose measurements present a higher correlation with the self-monitored blood glucose concentration and thereby, for example, the parameters of the sensor model can advantageously be determined more simply and accurately.

[0056] According to a further preferred embodiment, the state transition model comprises a diffusion model for time-dependent modeling of diffusion processes of glucose from the transport fluid to the surrounding tissue. A simple and at the same time computationally less intensive modeling of decay and time delays between the glucose level in the transport fluid, in particular in the blood, and the tissue glucose level is provided by means of a diffusion model, in particular a diffusion model based on a diffusion constant.

[0057] According to another preferred embodiment, the parameters of the sensor model and / or the state transition parameters of the state transition model are estimated and / or updated at least periodically. This has the advantage that, overall, the accuracy for determining the current glucose level is thereby increased; likewise, the parameters of the model in question can be flexibly adjusted to changing circumstances or influences.

[0058] Further important features and advantages of the invention emerge from the dependent claims, the drawings and the description of the corresponding figures using the drawings.

[0059] It is to be understood that the features mentioned above and those yet to be explained can be used not only in the respectively indicated combination but also in other combinations or alone, without departing from the scope of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Preferred designs and embodiments of the present invention are shown in the accompanying drawings and are further explained in the following description. All remodeling steps of equations, assumptions, solution procedures, etc. may be used individually without exceeding the scope of the present invention.

[0061] Figure 1 The steps of a method according to an embodiment of the present invention are shown in the form of a diagram;

[0062] Figure 2 The steps of a method according to an embodiment of the present invention are shown in the form of a diagram; and

[0063] Figure 3 A comparison between the method according to an embodiment of the present invention and a known method is shown in a diagram.

Claims

1. A method for continuously determining the current glucose level in a transport fluid of a biological subject, the method comprising the following steps: a) determining a series of measurements using a sensor device, the series of measurements comprising at least two temporally spaced measurements of tissue glucose levels in tissue surrounding the transport fluid, b) using the given series of measured values, determining the tissue glucose level based on a sensor model, wherein the measured values ​​of the sensor device are related to the tissue glucose level by means of the sensor model while taking into account measurement noise, c) providing a state transition model, wherein by means of the state transition model at least one glucose level in the transport fluid is related to the determined tissue glucose level while taking into account process noise, and d) determining a current glucose level based on the provided state transition model and the determined tissue glucose level, Wherein, at least step d) is performed using at least one moving horizon estimation method.

2. The method according to claim 1, characterized in that The sensor model is provided in the form of a linear function or a non-linear function between the measured value and the tissue glucose level.

3. The method according to claim 1, characterized in that The value of the horizon used to provide the rolling horizon estimate of the current glucose level is selected to be less than or equal to ten.

4. The method according to any one of claims 1 to 3, characterized in that at least regularly, estimating the variance of the measurement noise and / or the variance of the process noise, Therein, the variance of the measurement noise and / or the variance of the process noise is estimated based on at least one previous value using exponential smoothing.

5. The method according to claim 4, characterized in that Measured values ​​which are only partially used for calculating the estimation of the measurement noise and / or the process noise can be temporarily stored, and measured values ​​which are not temporarily stored and are required can be interpolated using the stored measured values.

6. The method according to claim 4, characterized in that The number of previous measurements is selected to be greater than the measurements of the horizon of the moving horizon estimation method.

7. The method according to claim 6, characterized in that The variance of the measurement noise and / or the variance of the process noise is regularly adjusted based on the level of the sum of the horizon of the rolling horizon estimation method and the number of previous measurements used to calculate the estimation of the measurement noise and / or the process noise.

8. The method according to claim 1, characterized in that: The measured values ​​provided by means of the filter function are filtered by means of the filter function, wherein errors of the sensor device are suppressed by means of the filter function.

9. The method according to claim 8, characterized in that The gradient of increase of the current tissue glucose level and / or the current tissue glucose level are evaluated to determine an error of the sensor device.

10. The method according to claim 8 or 9, characterized in that: Measurement values ​​provided below a predefinable low threshold level and / or above a predefinable high threshold level are filtered out by the filter function, the low threshold level and the high threshold level corresponding to physiological limits.

11. The method according to any one of claims 1 to 3 and 5 to 9, characterized in that After step d) has been carried out, a calibration of the measured values ​​of the sensor device is carried out.

12. The method according to any one of claims 1 to 3 and 5 to 9, characterized in that The state transition model includes a diffusion model for modeling the diffusion process of glucose from the transport fluid into the surrounding tissue in a time-dependent manner. and / or At least sensor model parameters of the sensor model and / or state transition parameters of the state transition model are estimated and / or updated regularly.

13. The method according to claim 1, characterized in that The transport fluid is blood.

14. The method according to claim 1, characterized in that Steps b) to d) are performed using the at least one moving horizon estimation method.

15. The method according to claim 1, characterized in that The rolling horizon estimation method is performed to provide a current glucose level in step d) and is applied to previously provided glucose measurements and to at least one previous tissue glucose measurement.

16. The method according to claim 4, characterized in that interpolating and / or weighting the variance of the measurement noise and / or the variance of the process noise at least regularly, Therein, the variance of the measurement noise and / or the variance of the process noise is interpolated and / or weighted based on at least one previous value using exponential smoothing.

17. The method according to claim 6, characterized in that A number of previous measurements is selected which is at least twice as large as the measurements of the horizon of the moving horizon estimation method.

18. The method according to claim 17, characterized in that The number of previous measurements is selected to be at least five times greater than the number of measurements of the horizon of the moving horizon estimation method.

19. The method according to claim 8, characterized in that By means of the filter function, measurement errors of the sensor arrangement are suppressed.

20. The method according to claim 8, characterized in that The measured values ​​are weighted by means of the filter function.

21. The method according to claim 10, characterized in that The low threshold level exhibits values ​​between 10 mg / dL and 50 mg / dL, and the high threshold level exhibits values ​​between 100 mg / dL and 600 mg / dL.

22. The method according to claim 21, characterized in that The low threshold level is 30 mg / dL and the high threshold level is 450 mg / dL.

23. A device for continuously determining the current glucose level in a transport fluid of a biological subject, the device being adapted to implement the method according to any one of claims 1 to 22, the device comprising: a sensor device for measuring fluorescence in tissue surrounding a transport fluid by means of a fiber optic probe, the sensor device being designed to determine a series of measurement values, the series of measurement values ​​comprising at least two measurement values ​​separated in time for the tissue surrounding the transport fluid, a providing device designed to provide a state transition model and to provide a sensor model, wherein by means of the state transition model at least one glucose level in the transport fluid is related to the determined tissue glucose level while taking into account process noise, wherein by means of the sensor model the measured values ​​of the sensor device are related to the tissue glucose level while taking into account measurement noise, An evaluation device is designed to determine the tissue glucose level based on the sensor model using the provided series of measurement values, and to determine the current glucose level based on the provided state transition model and the determined tissue glucose level using a rolling horizon estimation method.

24. The device according to claim 23, characterized in that The transport fluid is blood.

25. An evaluation device for continuously determining a current glucose level in a transport fluid of a biological subject, the evaluation device being adapted to perform a method according to any one of claims 1 to 22, the evaluation device comprising: at least one interface for connecting a sensor device for providing a series of measurements, the series of measurements comprising at least two temporally separated measurements of tissue glucose levels surrounding the transport fluid, at least one memory for storing a state transition model and for storing a sensor model, wherein at least one glucose level in the transport fluid is related to the tissue glucose level by means of the state transition model while taking into account at least one process noise level, wherein the measured values ​​of the sensor device are related to the tissue glucose level by means of the sensor model while taking into account at least one measurement noise, and A computing device designed to determine the tissue glucose level based on the sensor model using the provided series of measurements, and to determine the current glucose level based on the stored state transition model and the determined tissue glucose level using at least one rolling horizon estimation method.

26. The evaluation device according to claim 25, characterized in that The transport fluid is blood.

27. A non-volatile machine-readable medium for storing instructions which, when executed on a computer, cause a method for continuously determining a current glucose level in a transport fluid of a biological subject to be performed, adapted to perform the method according to any one of claims 1 to 22, the method comprising the steps of: a) determining a series of measurements using a sensor device, the series of measurements comprising at least two temporally separated measurements of tissue glucose levels in tissue surrounding the transport fluid, b) determining the tissue glucose level using the given series of measured values ​​based on a sensor model, wherein the measured values ​​of the sensor device are related to the tissue glucose level by means of the sensor model while taking into account measurement noise, c) providing a state transition model, wherein by means of the state transition model at least one glucose level in the transport fluid is related to the determined tissue glucose level while taking into account process noise, and d) determining said current glucose level based on the provided state transition model and the determined tissue glucose level, Wherein, at least step d) is performed using at least one moving horizon estimation method.

28. The non-volatile machine-readable medium of claim 27, wherein: The transport fluid is blood.

29. The non-volatile machine-readable medium of claim 27, wherein: Steps b) to d) are performed using the at least one moving horizon estimation method.

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