Abstract: A method for determining the reliability of an analyte sensor is disclosed. The analyte sensor is an in vivo sensor. The method includes measuring at least one first temperature dependent signal, measuring at least one second temperature dependent signal which is different from the first temperature dependent signal and which is related to a current flow in the analyte sensor, and correlating the first temperature dependent signal and the second temperature dependent signal for determining the reliability of the analyte sensor.

Abstract: A method for predicting blood glucose levels, in particular, for postprandial blood glucose level prediction, the method being computer-implemented and comprising: receiving a first medical data set of a patient covering a time range, the first medical data set comprising glucose data and further other medical data of the patient, extracting a second medical data set from the first medical data set, wherein the second medical data set is a subset of the first medical data set and wherein the extracting comprises at least one of: identifying duplicates in the first medical data set and removing identified duplicates, identifying data values that lie above a predefined maximum threshold data value or identifying data values that lie below a predefined minimum threshold data value and removing data associated with the identified data values, identifying data values that differ from predetermined expected data values by more than a predetermined amount and removing data associated with the identified data values,

Abstract: A method for screening a subject for the risk of chronic kidney disease (CKD) is provided. Marker data indicative for a plurality of marker parameters for a subject is received. The marker parameters indicate at least an age value, a time since diagnosis value indicative of a time since a diabetes diagnosis for the subject, a sample level of creatinine, an estimated glomerular filtration rate, a sample level of albumin, and a sample level of blood urea nitrogen. A risk factor is determined that indicates the risk of suffering CKD for the subject from the plurality of marker parameters.

Abstract: A method for generating a software-implemented module for determining a glucose value in a body fluid. A first set of input data indicative of first values measured for first and a second input parameters is provided. A second set of input data indicative of second values for the first and second input parameters is also provided. The first and second sets of input data are processed by a physiological model to determine first and second sets of glucose values, respectively, in a body fluid. Training data is determined and a set of test data different from the training data is also determined. A software-implemented machine learning model configured to determine a glucose value in a body fluid of a patient is provided and is trained by the training data and is tested by the test data.

Abstract: Methods and systems are disclosed for treating a person with diabetes by basal rate adjustment of insulin from a therapy delivery device based on risk associated with a glucose state of the person with diabetes. A method may include determining a current risk metric associated with a detected glucose state. The method may include determining a current risk metric associated with the detected glucose state based on a weighted average of cumulative hazard values of return paths generated from a glucose state distribution around a detected glucose state. The method may include calculating an adjustment to a basal rate of a therapy delivery device based on the current risk metric associated with the detected glucose state and a reference risk metric associated with a reference glucose level.

Abstract: A method for detecting an interferent contribution in a biosensor is disclosed. Herein, the biosensor has a first electrode (112), a second electrode, and a third electrode (114), wherein the first electrode (112) and the second electrode are covered by a membrane, wherein the first electrode (112) further includes an enzyme or wherein the first electrode (112) is covered by an enzyme layer. Further, the first electrode (112), the second electrode, and the third electrode (114) are connected via a potentiostat, wherein, in a normal operational mode, via the potentiostat an electrical potential difference is applied between the first electrode (112) and the second electrode in a manner that the first electrode (112) allows for oxidative processes and the third electrode (114) allows for reductive processes.

Abstract: A method providing a signal quality degree associated with an analyte value measured in a continuous monitoring system is disclosed. The method includes: receiving a measured analyte value from a biosensor; determining at least two impact parameters, wherein each of the impact parameters is influenced by an operational status of the continuous monitoring system and wherein each of the impact parameters is capable of exerting an influence on the signal quality of the biosensor and wherein the influence of each of the impact parameters on the signal quality of the biosensor is expressed by a weight assigned to each of the impact parameters; and determining the signal quality degree associated with the measured analyte value as a function of the weights and the corresponding impact parameters; and providing the signal quality degree associated with the analyte value. A method of calibration using the signal quality degree is also disclosed.

Abstract: Methods are provided for deriving/determining an analyte concentration that include recording measurement values during a time development indicating a progress of a detection reaction of at least one test substance and a body fluid sample and providing at least one measurement curve F(t) containing the measurement values, where the detection reaction is known to be influenced by the analyte concentration and at least one disturbance variable Y. The methods also include deriving an end value of the measurement curve to form a first variable x1, and deriving at least one fit parameter by taking into account an exponential characteristic of the measurement curve, and where the fit parameter forms at least one second variable x2. The methods further include deriving/determining the analyte concentration by using at least one multivariate evaluation algorithm adapted to combine x1 and x2. Also provided are computer programs and devices that incorporate the same.

Abstract: Methods are provided for detecting an analyte concentration/presence in a body fluid sample that include providing a set of at least two different evaluation rules, each evaluation rule adapted to derive a set characteristic values from an optical measurement curve, where at least one first characteristic value is derived from at least one first evaluation rule and at least one second characteristic value is derived from at least one second evaluation rule. The methods also include performing at least one multivariate analysis of the at least one first and second characteristic values by using at least one predetermined multivariate evaluation algorithm to derive at least one estimate value for at least one target variable Y of the state variables. The methods also include determining at least one analyte concentration by using the at least one target variable Y. Also provided are computer programs and devices that incorporate the same.

Abstract: The invention concerns a method and an apparatus for determining the concentration of an analyte in a body fluid, where the following measures are proposed: providing a layered test element (12) including an enzyme-based chemistry layer which is responsive to the analyte by a color change, applying a sample of the body fluid onto the test element (12), detecting by means of a photometric reflectance measuring device (16) a reflectance value of the test element (12), correcting the measured reflectance value by a predetermined offset value attributed to the test element (12), determining a concentration value of the analyte using the offset-corrected reflectance value.

Abstract: Methods, devices and systems for detecting an analyte in a body fluid are described. A sample of body fluid is applied to a test element having a test field including a test material adapted to change a measurable property in the presence of the analyte. The test element includes a capillary to guide the sample across said test field. The measurable property is measured in a first measurement location providing a first measurement value, and in a second measurement location providing a second measurement value. The analyte is detected by using an evaluation algorithm having at least a first input variable including a difference between the first measurement value and the second measurement value, and at least a second input variable including information relating to an analyte-induced change of the measurable property of the test material in at least part of the test field.

Abstract: Methods for detecting an analyte in a body fluid are described as well as devices and systems adapted for performing such methods. In embodiments of the method, a sample of body fluid is applied to a test element having at least one test field including at least one test material that is adapted to change at least one measurable property in the presence of the analyte. The test element further includes a capillary to guide the sample across said test field in a flow direction. The test element also includes first and second measurement locations offset from each other in the flow direction. The measurable property is measured in at least one first measurement location, providing at least one first measurement value, and it is measured in at least one second measurement location, providing at least one second measurement value.

Abstract: The present disclosure refers to a method for determining a blood glucose level for a patient, the method comprising detecting a present sensor signal in a present continuous interstitial blood glucose measurement for a patient; providing measurement data representing the present sensor signal; providing sensor signal correction data representing a patient-specific signal correction, the sensor signal correction data being determined from a former interstitial blood glucose measurement for the patient and comprising at least one of time delay data representing a patient-specific time delay ?t between a blood glucose value measured in a continuous interstitial blood glucose measurement and a blood glucose reference value measured in a capillary blood glucose measurement, and sensor sensitivity data representing, for the patient, a patient-specific sensor sensitivity for the sensor, determining corrected measurement data representing a corrected present sensor signal by applying the sensor signal correction dat

Abstract: A method providing a signal quality degree associated with an analyte value measured in a continuous monitoring system is disclosed. The method includes: receiving a measured analyte value from a biosensor; determining at least two impact parameters, wherein each of the impact parameters is influenced by an operational status of the continuous monitoring system and wherein each of the impact parameters is capable of exerting an influence on the signal quality of the biosensor and wherein the influence of each of the impact parameters on the signal quality of the biosensor is expressed by a weight assigned to each of the impact parameters; and determining the signal quality degree associated with the measured analyte value as a function of the weights and the corresponding impact parameters; and providing the signal quality degree associated with the analyte value. A method of calibration using the signal quality degree is also disclosed.

Abstract: A method for providing a signal quality degree associated with an analyte value measured in a continuous monitoring system is disclosed. The method includes the steps of: receiving a measured analyte value from a biosensor; determining at least two impact parameters, wherein each of the impact parameters is influenced by an operational status of the continuous monitoring system and wherein each of the impact parameters is capable of exerting an influence on the signal quality of the biosensor and wherein the influence of each of the impact parameters on the signal quality of the biosensor is expressed by a weight assigned to each of the impact parameters; and determining the signal quality degree associated with the measured analyte value as a function of the weights and the corresponding impact parameters; and providing the signal quality degree associated with the analyte value. Further methods are also disclosed.

Abstract: Methods are provided for deriving/determining an analyte concentration that include recording measurement values during a time development indicating a progress of a detection reaction of at least one test substance and a body fluid sample and providing at least one measurement curve F(t) containing the measurement values, where the detection reaction is known to be influenced by the analyte concentration and at least one disturbance variable Y. The methods also include deriving an end value of the measurement curve to form a first variable x1, and deriving at least one fit parameter by taking into account an exponential characteristic of the measurement curve, and where the fit parameter forms at least one second variable x2. The methods further include deriving/determining the analyte concentration by using at least one multivariate evaluation algorithm adapted to combine x1 and x2. Also provided are computer programs and devices that incorporate the same.

Abstract: Methods are provided for detecting an analyte concentration/presence in a body fluid sample that include providing a set of at least two different evaluation rules, each evaluation rule adapted to derive a set characteristic values from an optical measurement curve, where at least one first characteristic value is derived from at least one first evaluation rule and at least one second characteristic value is derived from at least one second evaluation rule. The methods also include performing at least one multivariate analysis of the at least one first and second characteristic values by using at least one predetermined multivariate evaluation algorithm to derive at least one estimate value for at least one target variable Y of the state variables. The methods also include determining at least one analyte concentration by using the at least one target variable Y. Also provided are computer programs and devices that incorporate the same.

Abstract: The disclosure relates to a method and system for controlling glucose levels comprising receiving behavioral sensor measurements and analyte sensor measurements, determining a plurality of analyte profiles from continuous analyte sensor measurements; grouping the plurality of analyte profiles into clusters; assigning a selected behavioral parameter or a selected pattern of behavioral parameters to each analyte profile in a first cluster, and providing a treatment recommendation.

Abstract: Methods and systems are disclosed for treating a person with diabetes by basal rate adjustment of insulin from a therapy delivery device based on risk associated with a glucose state of the person with diabetes. A method may include determining a current risk metric associated with a detected glucose state. The method may include determining a current risk metric associated with the detected glucose state based on a weighted average of cumulative hazard values of return paths generated from a glucose state distribution around a detected glucose state. The method may include calculating an adjustment to a basal rate of a therapy delivery device based on the current risk metric associated with the detected glucose state and a reference risk metric associated with a reference glucose level.

Abstract: A method and system of determining a basal rate adjustment of insulin in a continuous glucose monitoring system of a person with diabetes is provided. The method includes receiving, by at least one computing device, a signal representative of at least one glucose measurement; detecting, by the at least one computing device, a glucose state of the person based on the signal, the detected glucose state including a glucose level of the person and a rate of change of the glucose level; determining, by the at least one computing device, a current risk metric, the current risk metric indicating a risk of at least one of a hypoglycemic condition and a hyperglycemic condition of the person; and calculating, by the at least one computing device, an adjustment to a basal rate of a therapy delivery device based on the current risk metric and a control-to-range algorithm comprising at least one aggressiveness parameter.