Abstract: Various embodiments that allow a more accurate electrochemical test strip measurement by identifying erroneous output signals during a glucose measurement thereby ensuring a much more accurate glucose test system.

Abstract: Various embodiments that allow a more accurate electrochemical test strip measurement by identifying erroneous output signals during a glucose measurement thereby ensuring a much more accurate glucose test system.

Abstract: Various embodiments of a technique to sample output signals at different time intervals from each of the electrodes in a biosensor to obtain respective glucose estimates including one where the output signals of at least one combination of electrodes measured at various time intervals are summed together to provide for a combined glucose estimate.

Abstract: Described and illustrated herein are systems and exemplary methods of operating an analyte measurement system having a meter and a test strip. In one embodiment, the method may be achieved by applying a first test voltage between a reference electrode and a second working electrode and applying a second test voltage between the reference electrode and a first working electrode; measuring a first test current, a second test current, a third test current and a fourth test current at the second working electrode after a blood sample containing an analyte is applied to the test strip; measuring a fifth test current at the first working electrode; estimating a hematocrit-corrected analyte concentration from the first, second, third, fourth and fifth test currents; and annunciating the hematocrit-corrected analyte concentration.

Abstract: Various embodiments for a method, systems and meters that allow for a more accurate analyte concentration with a biosensor by determining at least one physical characteristic of the sample and compensating for the effects of ambient temperature with a defined relationship between temperature in the environment, the meter or the biosensor.

Abstract: Various embodiments for systems and methods that allow for a more accurate analyte concentration with a biosensor by obtaining two calibration codes, one for batch calibration due to manufacturing variations and the other for time calibration due to measured physical characteristics of the fluid sample.

Abstract: Various embodiments for methods and systems that allow for a more accurate analyte concentration with a biosensor by determining at least one physical characteristic of the sample containing the analyte and deriving one of a batch slope, sampling time, or combinations thereof to attain accurate glucose concentration.

Abstract: Various embodiments that allow for a more accurate analyte concentration by determining at least one physical characteristic, particularly hematocrit, of the blood sample containing the analyte, particularly glucose, and deriving a specific sampling time based on a relationship between the physical characteristic and sampling time so that the analyte concentration can be determined with greater accuracy with the specific sampling time point.

Abstract: Various embodiments for a method that allow for a more accurate analyte concentration with a biosensor by determining at least one physical characteristic, typically hematocrit, of the sample containing the analyte and deriving from this characteristic a parameter relating to the biosensor to attain accurate glucose concentration.

Abstract: Described are methods and systems to apply a plurality of test voltages to the test strip and measure at least a current transient output resulting from an electrochemical reaction in a test chamber of the test strip so that a glucose concentration can be determined that are generally insensitive to other substances in the body fluid sample that could affect the precision and accuracy of the glucose concentration.

Abstract: Described are methods and systems to apply a plurality of test voltages to the test strip and measure at least a current transient output resulting from an electrochemical reaction in a test chamber of the test strip so that a glucose concentration can be determined that are generally insensitive to other substances in the body fluid sample that could affect the precision and accuracy of the glucose concentration.

Abstract: A diabetes management system and method are provided herein that may be used to analyze a patient's level of control of their diabetes, by looking at the difference between blood glucose measurements taken before and after a meal. If the standard deviation of the differences D calculated between pre- and post-prandial results is found to vary significantly from a predetermined threshold value, then a message or graphical indication may be displayed to the user. Messages may provide suggestions to the user as to ways to better manage their condition to ensure compliance of any prescribed diabetes regimen or to guide the patient in managing their diabetes.

Abstract: Described and illustrated herein are systems and exemplary methods of operating an analyte measurement system having a meter and a test strip. In one embodiment, the method may be achieved by applying a first test voltage between a reference electrode and a second working electrode and applying a second test voltage between the reference electrode and a first working electrode; measuring a first test current, a second test current, a third test current and a fourth test current at the second working electrode after a blood sample containing an analyte is applied to the test strip; measuring a fifth test current at the first working electrode; estimating a hematocrit-corrected analyte concentration from the first, second, third, fourth and fifth test currents; and annunciating the hematocrit-corrected analyte concentration.

Abstract: Described and illustrated herein are systems and exemplary methods of operating an analyte measurement system having a meter and a test strip. In one embodiment, the method may be achieved by applying a first test voltage between a reference electrode and a second working electrode and applying a second test voltage between the reference electrode and a first working electrode; measuring a first test current, a second test current, a third test current and a fourth test current at the second working electrode after a blood sample containing an analyte is applied to the test strip; measuring a fifth test current at the first working electrode; estimating a hematocrit-corrected analyte concentration from the first, second, third, fourth and fifth test currents; and annunciating the hematocrit-corrected analyte concentration.

Abstract: A method for predicting a user's future glycemic state includes measuring a user's glucose concentration at intervals over a time duration, thereby generating a plurality of glucose concentrations as a function of time. First and second glucose prediction equations that are fits to the plurality of glucose concentrations based on first and second non-identical mathematical models, respectively, are then derived. The method also includes calculating first and second predicted glucose concentrations at a future time using the first and second glucose prediction equations, respectively. Thereafter, an average predicted glucose concentration and a merit index are calculated based on the first and second predicted glucose calculations. The plurality of glucose concentrations as a function of time, the merit index and average predicted glucose concentration are input into a trained model (for example, a Hidden Markov Model) that outputs a set of glucose concentration probabilities.

Abstract: A medical device for predicting a user's future glycemic state includes a memory module, a processor module and a user alert module. The memory module is configured to receive and store a plurality of glucose concentrations as a function of time that were generated by a user's use of a continuous glucose monitor. The processor module is configured to derive first and second glucose prediction equations that are fits to the plurality of glucose concentrations stored in the memory module with the fits being based on first and second mathematical models, respectively. The processor module is also configured to calculate first and second predicted glucose concentrations at a future time using the first and second glucose prediction equations, respectively, and to also calculate an average predicted glucose concentration and a merit index based on the first and second predicted glucose calculations.

Abstract: A soil sample of fixed volume is mixed with a drying agent (MgSO4) and then acetone. The liquid is filtered off and a sample is applied to the sensing surface of an attenuated total reflectance (ATR) device in an IR spectrometer. After evaporation of the acetone, absorption is measured in a C-H stretch region (e.g. 2950 cm?1) to provide a value indicative of the amount of oil in the sample.

Abstract: A medical device for predicting a user's future glycemic state includes a memory module, a processor module and a user alert module. The memory module is configured to receive and store a plurality of glucose concentrations as a function of time that were generated by a user's use of a continuous glucose monitor. The processor module is configured to derive first and second glucose prediction equations that are fits to the plurality of glucose concentrations stored in the memory module with the fits being based on first and second mathematical models, respectively. The processor module is also configured to calculate first and second predicted glucose concentrations at a future time using the first and second glucose prediction equations, respectively, and to also calculate an average predicted glucose concentration and a merit index based on the first and second predicted glucose calculations.

Abstract: A method for predicting a user's future glycemic state includes measuring a user's glucose concentration at intervals over a time duration, thereby generating a plurality of glucose concentrations as a function of time. First and second glucose prediction equations that are fits to the plurality of glucose concentrations based on first and second non-identical mathematical models, respectively, are then derived. The method also includes calculating first and second predicted glucose concentrations at a future time using the first and second glucose prediction equations, respectively. Thereafter, an average predicted glucose concentration and a merit index are calculated based on the first and second predicted glucose calculations. The plurality of glucose concentrations as a function of time, the merit index and average predicted glucose concentration are input into a trained model (for example, a Hidden Markov Model) that outputs a set of glucose concentration probabilities.

Abstract: For the determination of analytes in body fluids, voltammetry using a simple, non-selective, electrode sensor system has been found to work. The signal is desirably processed by a technique such as neural network analysis, which can permit plural analytes to be determined simultaneously.